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Aircraft Systems Diagnostics, Prognostics and Health Management Technology Insight Document Industry Canada Contract 5011101 Version: 0.2 (DRAFT) Date: 16 December 2004

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Page 1: Aircraft Systems

Aircraft Systems Diagnostics, Prognostics and Health Management Technology Insight Document Industry Canada Contract 5011101 Version: 0.2 (DRAFT) Date: 16 December 2004

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Table of Contents Table of Contents............................................................................................................... i 1 Introduction ................................................................................................................1

1.1 Background .......................................................................................................1 1.2 Aircraft Diagnostics, Prognostics and Health Management ..............................1 1.3 Aircraft Sub-systems .........................................................................................2

1.3.1 Aero-propulsion Systems ..............................................................................2 1.3.2 Aircraft Structures..........................................................................................2 1.3.3 Ancillary Systems ..........................................................................................2 1.3.4 DPHM Systems Integration ...........................................................................3

1.4 Vision.................................................................................................................3 1.5 Mission ..............................................................................................................3 1.6 Document Outline..............................................................................................4

2 Methodology ..............................................................................................................4 2.1 Technology Roadmapping ................................................................................5 2.2 Technology Insertion Roadmapping (TIRM) .....................................................5 2.3 Aerospace and Defence Technology Framework .............................................6

3 Market Drivers and Constraints .................................................................................6 3.1 Market Sectors ..................................................................................................6

3.1.1 Military Aircraft...............................................................................................6 3.1.2 Commercial Aircraft .......................................................................................6 3.1.3 Regional and Corporate Aircraft ....................................................................7

3.2 Market Drivers ...................................................................................................7 3.2.1 Cost of Ownership.........................................................................................7 3.2.2 Reliability and Availability ..............................................................................8 3.2.3 Airworthiness.................................................................................................9

3.3 Market Constraints ............................................................................................9 4 System Requirements..............................................................................................11

4.1 Systems Requirement Overview .....................................................................11 4.2 System Requirements Map .............................................................................13

5 DPHM Technologies ................................................................................................14 6 Canadian DPHM Capabilities and Gaps..................................................................15

6.1 Market Focus...................................................................................................15 6.1.1 Military Aircraft.............................................................................................15 6.1.2 Commercial Aircraft .....................................................................................15 6.1.3 Regional Aircraft ..........................................................................................15

6.2 DPHM Capabilities ..........................................................................................15 6.2.1 Military Aircraft.............................................................................................15 6.2.2 Commercial Aircraft .....................................................................................15 6.2.3 Regional Aircraft ..........................................................................................15

6.3 Canadian DPHM Gap Assessment .................................................................15 7 Technology Implementation Opportunities ..............................................................16

7.1 DPHM Working Group.....................................................................................16 7.2 Technology Demonstration Projects Overview ...............................................16 7.3 BHTI1 - Individual Aircraft Usage Monitoring ..................................................19 7.4 BHTI2 - Development of Structures with Embedded Sensors.........................20 7.5 CB1 - FMEA/Field Diagnostic Interoperability .................................................21 7.6 CB2 - Interpretation of Trends and Multivariate Correlations ..........................22 7.7 HW - DPHM Requirements for Aircraft Subsystems .......................................23

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7.8 NP1 - Development of a 3D Standoff Scanner for Aircraft NDI .......................24 7.9 NP2 - Develop a 3D Non-contact System for Measuring Airframe Deflections during Testing..............................................................................................................25 7.10 NP3 - Develop a Rapid 3D Non-contact System Capable of Reverse Engineering of As-Built and As-Repaired Aircraft........................................................26 7.11 LPTI - Prognosis and Emission Mitigation for DPHM Infrastructure................27 7.12 SAL - Develop and Demonstrate DPHM Benefits on Legacy Fleet.................28 7.13 PWC1 - Maintenance Intervention Planning ...................................................29 7.14 PWC2 - Maintainability Tracking and Rapid Maturing Process.......................30 7.15 PWC3 - Test Results Monitoring and Diagnostics ..........................................31 7.16 PWC4 - Micro-electromechanical (MEMS)Systems for Fire Detection ...........32 7.17 PWC5 - Mobile Phone Engine Data Transfer..................................................33 7.18 PWC6 - Wireless New Engine Sensors ..........................................................34

8 Recommendations ...................................................................................................35 9 Definitions ................................................................................................................36 10 References ..........................................................................................................38 Annex A - Inventory of Relevant DPHM Activities...........................................................39 Annex B - Aeropropulsion DPHM Requirements and Technology Descriptors ..............53 B1 Systems Requirements..............................................................................................53

B1.1 Systems Requirements Overview ......................................................................53 B1.2 System Functionality Map ...................................................................................54 B1.3 Data Collection and Communication..................................................................55 B1.4 Diagnostics.........................................................................................................55

B1.5 Fault Detection ...............................................................................................55 B1.6 Fault Isolation .................................................................................................55

B1.7 Prognostics ........................................................................................................56 B1.7.1 Failure Mode, Effects and Criticality Analysis (FMECA)..............................56 B1.7.2 Component Life Tracking ............................................................................57 B1.7.3 Life Remaining Analysis ..............................................................................58 B1.7.4 Performance Trending.................................................................................59 B1.7.5 Fault Prediction............................................................................................59

B1.8 Health Management...........................................................................................59 B1.8.1 Fault Assessment ........................................................................................60 B1.8.2 Fault Reporting ............................................................................................60 B1.8.3 Supply Chain Integration .............................................................................60 B1.8.4 Fault Accommodation..................................................................................60

B2 Technologies ............................................................................................................61 B2.1 Advanced DPHM Technologies Overview .........................................................61 B2.2 Metallurgical Life Limit Monitoring......................................................................62 B2.3 Crack Detection and Monitoring.........................................................................63 B2.4 Oil Debris Monitoring..........................................................................................64 B2.5 Gas Path Debris Monitoring ...............................................................................64 B2.6 Vibration Analysis...............................................................................................65 B2.7 Physical Alignment.............................................................................................66

B2.7.1 Clearances ..................................................................................................66 B2.7.2 Aero-thermodynamic Performance Assessment .........................................66

B2.8 Decision Aids/Reasoning Engines .....................................................................67 B2.8.1 Rules Based Reasoning..............................................................................67 B2.8.2 Case Based Reasoning...............................................................................67 B2.8.3 Model Based Reasoning .............................................................................68 B2.8.4 Neural Networks ..........................................................................................68

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B2.9 Knowledge Discovery and Data Mining .............................................................68 B2.10 Data Fusion......................................................................................................69 B2.11 Health Management/Supply Chain Integration ................................................69

B2.11.1 Integrated Maintenance Decision Environment.........................................69 B2.11.2 Competency Assessment and Just-In-Time Training................................69

Annex C – DPHM Standing Working Group Steering Committee Terms of Reference..71 Annex D – Aircraft DPHM Montreal Workshop Attendee List .........................................73 Annex E – Aircraft DPHM Ottawa Workshop Attendee List ............................................75

List of Tables

Table # Title Page

1 Aircraft Systems DPHM Systems Requirements Map 13

2 Aircraft Systems DPHM Technologies Map 14

3 DPHM Technology Insertion Project Summary Table 17-18

B-1 DPHM Top Level System Functionality Map 54

B-2 Advanced JSF Condition Based Maintenance Technologies 61

List of Figures

Figure #

Title Page

1 The Technology Roadmap Process

5

2 Representative DPHM System Block Diagram - JSF 11

3 Representative DPHM System Block Diagram – Rotorcraft (M. Augustin, Bell Helicopters, November 18th, 2004)

12

B-1 DPHM Systems Evolution 54

B-2 F100 Seeded Fault Engine Test DPHM Technologies 58

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1 Introduction

1.1 Background This Technology Insight Document is the product of collaboration between Industry Canada, the Canadian aerospace industry and the Aerospace Industries Association of Canada (AIAC). The objective of this activity is to enhance Canadian Aerospace and Defence sector competitiveness through coordinated and focused government/industry strategic interaction in the area of Diagnostics, Prognostics and Health Management (DPHM) for aircraft and aircraft systems.

The requirement for this DPHM initiative was identified through consultation with industry and government stakeholders. This activity builds on existing Canadian industry sector strengths to support a number of national and international legacy as well as advanced technology programs, most notably the Joint Strike Fighter (JSF). While the JSF is not the sole focus of this report, that program has substantively advanced DPHM technology concepts into an integrated systems approach beginning at the earliest design stages. The JSF Prognostics and Health Management (PHM) system is considered an “intellectual process leader” within the US DoD and is used extensively in this document for reference and guidance. Annex A to this document provides a listing and website references for a number of relevant DPHM R&D activities or organizations and programs that are supporting DPHM relevant activities.

1.2 Aircraft Diagnostics, Prognostics and Health Management There has long been a high level of market need, and demand is accelerating significantly for broader and more effective integrated diagnostic, prognostic and health management systems. This demand is industry pervasive from regional aircraft where Canada has particular strengths and interests, to advanced military systems including the JSF, as well as such initiatives as the Versatile Affordable Advanced Turbine Engines (VAATE) program. It should be noted that rotary wing aircraft which provided significant impetus to this technology domain in the early 80’s as a result of North Sea oil servicing flight mishaps, continue to define extreme diagnostic and prognostic technology challenges in support of aircraft such as the V-22 Osprey and Bell 609 as well as conventional rotorcraft.

The technical challenges are numerous and apply to a broad spectrum of primary and enabling technologies each of which has specific health and usage monitoring sensor and data management requirements. While this study does address the individual sensor or analysis technologies that have been developed for specific aircraft and their systems, a primary focus of this technology project will be the integration of the numerous disparate systems capabilities into an effective and efficient integrated technology and enterprise system. It is this Health Management aspect of DPHM that encompasses the enterprise integration functionality as maintenance decisions will increasing be made on-board aircraft, and rectification planning decisions taken in an increasingly automated fashion.

A few basic definitions and terminology on which this project is based are provided below and are largely derived from JSF terminology. It is noted that the JSF does not separate diagnostics from the health management concept. This study identifies diagnostics as a separate concept to capture those processes and technologies that are applied to legacy aircraft systems where DPHM processes or systems are often introduced after the aircraft has entered operational service.

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• Diagnostics – is the process of determining the state of a component to perform its function(s) based on observed parameters;

• Prognostics – is predictive diagnostics which includes determining the remaining life or time span of proper operation of a component; and

• Health Management – is the capability to make appropriate decisions about maintenance actions based on diagnostics/prognostics information, available resources, and operational demand.

1.3 Aircraft Sub-systems To address differing DPHM needs and technology enablers the aircraft will be partitioned into four sub-system or conceptual groupings which are listed immediately following and further described in subsequent paragraphs:

• Aero-propulsion systems;

• Aircraft structures;

• Ancillary systems; and

• DPHM systems integration components.

1.3.1 Aero-propulsion Systems Aero-propulsion systems are considered to encompass the primary and auxiliary power units on an aircraft including relevant subsystems and include:

• Primary propulsion units used to generate thrust or lift indirectly;

• Auxiliary propulsion units, typically gas turbines, that are used to generate customer services including pneumatic or electric services;

• Gearboxes, driveshafts or other mechanical systems that are driven by primary or auxiliary power units; and

• Propellers, ducted fans and helicopter rotor blades or other thrust or lift generating devices of a similar nature.

1.3.2 Aircraft Structures Although the term aircraft structures can be taken to include all structural elements of an aircraft and it’s subsystems, for the purposes of this initiative, the aircraft structure is considered to consist of the airframe including: fuselage, wings, flight controls surfaces, and the main and tail rotors of a rotary-wing aircraft. Structural materials of interest include metallics, plastics, composites of all forms and types, and hybrid materials.

1.3.3 Ancillary Systems The ancillary systems category is intended to capture all other aircraft sub-systems for which DPHM technologies are deemed necessary from economic, reliability or safety perspectives. A partial list of these systems includes the following:

• Environmental control systems;

• Electric power and power distribution systems;

• Brakes;

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• Wheels and tires;

• Fuel and fuel distribution systems;

• Hydraulic systems; and

• Military aircraft specific systems.

Note that avionics systems are not specifically included in the above listing as their reliability is such that typical Mean-Time-Between-Failure (MTBF) for aviation electronics components often represents a significant portion of the total aircraft service life, and these systems are characteristically well served by built-in-test functionality that provides highly discriminating failure information.

1.3.4 DPHM Systems Integration A final functional component is introduced to address the information technology and systems integration concepts and technologies that are necessary to effectively capture and communicate DPHM information to both on-board and off-board systems and processes.

This technology component also includes adaptive control concepts for all aircraft systems. While adaptive control technologies have been widely implemented in certain areas, there is always the potential for expanding functionality of adaptive control strategies to other systems.

1.4 Vision A proposed vision statement follows:

“The Canadian aerospace industry is globally recognized as a preferred source of diagnostics, prognostics and health managements systems, products and services.”

1.5 Mission World-class Canadian DPHM systems, products, and services will be developed, refined and demonstrated through a number of technology demonstration projects that are structured within a focused Technology Implementation Program.

Specific objectives for the DPHM Technology Implementation Program are as follows:

• Identify, research, and prioritize critical system requirements and performance goals;

• Define and prioritize DPHM sub-system technologies, as well as pervasive technology areas;

• Identify, assess and rank in terms of importance DPHM market drivers, technology drivers, and product feature concepts;

• Identify and quantify Canadian and global technology capabilities and characterize any current and significant gaps in the Canadian Aerospace sector; and

• Define a DPHM Technology Implementation Program involving one or more DPHM technology demonstration projects.

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1.6 Document Outline This document is presented in the following order:

• Introduction: In the introductory section, the background to this activity is provided to scope the project in terms of functionality and systems application.

• Methodology: Technology roadmapping and a new and rapid roadmapping process called the Technology Insertion Roadmap (TIRM) are described in order to situate the reader with respect to the TID which is the first step in the TIRM process.

• Market Drivers: The market requirements by sector for DPHM systems functionality are briefly described.

• System Requirements: The overall DPHM environment is discussed in terms of major functional requirements.

• Technologies: Technologies, both primary and enabling, are described in the context of global and Canadian aerospace environments.

• Canadian Gap Assessment: Based on DPHM market drivers, system requirements and the technology requirements, an overview of Canadian strengths will be presented so that areas where focused investment would provide greatest impact in this market segment can be identified.

• Concluding material: Conclusions and recommendations for future or follow-on activities are presented. The concluding material also includes the initial description of the Technology Implementation Program with insertion projects briefly introduced. References and terminology/definitions are also provided in the concluding material.

• DPHM Global Activity Inventory: Annex A provides a listing of the DPHM activities, or organizations that support DPHM activities that have been considered in the generation of this Technology Insight Document. There is no intent to provide an exhaustive description of these projects or organizations but rather to provide website or document content that can be used by readers of this document in performing additional individual research.

• Aeropropulsion Systems Requirements and Technology Descriptors: Annex B contains the systems requirements and technology narratives from the original Aeropropulsion and Aircraft Mechanical Systems Technology Insight Document Version 0.3 dated 19 March 2004.

• DPHM Standing Working Group Steering Committee Terms of Reference: Annex C contains proposed terms of reference for a Steering Committee whose purpose is to organize a standing DPHM Working Group.

• Aircraft DPHM Montreal Workshop Attendee List: Annex D contains a listing of attendees at the Montreal DPHM Workshop held on June 22nd, 2004 and their contact informaton.

• Aircraft DPHM Ottawa Workshop Attendee List: Annex E contains a listing of attendees at the Ottawa DPHM Workshop held on November 18th, 2004 and their contact informaton.

2 Methodology This DPHM initiative forms an element of a cohesive and far-ranging strategy implemented by Industry Canada and AIAC. It is founded on the Aerospace and Defence Technology Framework as well as an abbreviated Technology Roadmapping process that has been developed and trialled by Industry Canada and AIAC.

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The roadmapping process is first described in general terms in order to understand the abbreviated process which is used herein - Technology Insertion Roadmapping (TIRM). The Aerospace and Defence Technology Framework is also briefly described as it is considered to be a foundation document to this effort.

2.1 Technology Roadmapping The technology roadmap as a process originated in the early 1980’s when companies such as Motorola began to utilize roadmapping to ensure that short, medium and long term product development and technology issues were well understood and that investment was apportioned appropriately. Industry Canada began their roadmap initiative in 1995 and published a document entitled “Technology Roadmapping: A Guide for Government Employees” [1]. Other reference information on the Technology Roadmap Process can be found at the Sandia National Laboratories website [2].

Since 1995, the Government of Canada has sponsored or participated in a significant number of technology roadmaps. One of these was the “Aircraft Design, Manufacturing and Repair & Overhaul (Ontario Pilot)” roadmap which was conducted in 1996 [3]. This pilot project roadmap identified a number of key topics of interest and also contributed to the definition of need for this DPHM project. In the Pilot Roadmap study, Integrated Health and Usage Monitoring was identified as one of the 6 “Critical” Maintenance, Repair and Overhaul technologies.

The roadmapping process is described in the following diagram to situate the reader in terms of where this study fits within the overall Industry Canada roadmapping and TIRM processes:

Figure 1 – The Technology Roadmap Process

2.2 Technology Insertion Roadmapping (TIRM) The TIRM is a high impact technology roadmap that is performed in an abbreviated timeframe, typically six months. The more conventional roadmap process as defined at [1] will be completed in 24 months at a cost of $200K or more, excluding the costs of in-kind government and industry participation. A TIRM may be appropriate if a significant quantity of reference

Step 1 – Demand Side

Identify market drivers and characteristics that will define demand in the market in the period 2004-2009. Step 2 – Supply Side

Identify the functional /performance requirements and characteristics necessary to capture market share.

Step 3 – Technology

Identify technology capabilities, gaps and priorities that need to be addressed to deliver the required products.

Step 4 – Follow Up

Generate a Technology Roadmap Report, initiate technology implementation. And periodically review the roadmap.

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material already exists, and roadmap or roadmap-like activities have already been pursued in Canada or elsewhere. Simply stated, the focus of the TIRM is to define a Technology Implementation Program that will consist of one or more technology insertion projects. The TIRM follows the same process as the more conventional roadmap, although a number of steps, including consultations, may be streamlined.

This project addresses the first three steps in the TIRM and culminates in the generation of the TID. The TID is refined in the fourth step of the TIRM, although the primary intent of the last step in the TIRM is to generate a Technology Implementation Program that consists of one or more technology insertion projects.

2.3 Aerospace and Defence Technology Framework The reader is invited to review the Aerospace and Defence Technology Framework [4] which serves as a foundation document for this TIRM process and which will be continuously improved through the performance of this and future roadmapping activities.

The Aerospace and Defence Technology Framework provides a common lexicon and understanding of the aerospace and defence technology structure and definitions. The Technology Framework begins by defining a technology evolutionary cycle and terminology for each of the phases. The definition of the technology development cycle provides clarification on those phases where government investment emphasis and interest is desired and appropriate.

3 Market Drivers and Constraints

3.1 Market Sectors The need for, and implementation of DPHM concepts and systems will be influenced by market sector characteristics. Three market sectors are defined for the purposes of this study as follows:

• Military aircraft;

• Commercial aircraft; and

• Regional and corporate aircraft.

3.1.1 Military Aircraft Military aircraft users are typically early adopters of technology and often significantly underwrite the cost of developing and proving new technologies. This market segment includes all aircraft and rotorcraft that are used by military or paramilitary users but excluding those aircraft that are commercially certificated and used by the military in a manner similar to that of a commercial operator.

3.1.2 Commercial Aircraft This market segment is characterized by large, typically twin aisle, aircraft that are used for long flights of durations greater than 3 hours as well as narrow-body or single aisle aircraft. Aircraft acquisition and operational costs are such that the cost of implementing DPHM technologies can often be readily substantiated. Guaranteed operational cost programs however, will tend to shift the responsibility for DPHM systems from the operator of these large commercial aircraft to the MR&O services providers.

By way of example, in a recent presentation, Mr Jean-Pierre Daniel, from Airbus Industries pointed out that structural health management technologies have advanced to the point where

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broader application of these technologies can provide significant benefits in a number of areas. His contention is that the ultimate benefit to be derived from HM technologies will be in structural design optimization yielding weight savings and more energy efficient aircraft. More immediate benefits are to be derived from quicker and more reliable maintenance inspections.

3.1.3 Regional and Corporate Aircraft This segment comprises 50-90 seat aircraft that are normally termed “regional”, as well as aircraft that are used in corporate fleets. The emphasis on low cost of ownership poses challenges to the introduction of DPHM technologies although longer term service contracts may justify the introduction of DPHM technologies from warranty and fractional ownership usage tracking perspectives.

3.2 Market Drivers Aircraft are extremely complex “systems of systems” whose costs of acquisition and operation are significant in all market sectors. The statement that cost reduction or avoidance is a primary market driver may seem self-evident, however the situation is made more complex when one considers the differences in accounting approaches between the military or civilian aircraft operator, or when viewed from the perspective of the various stakeholders in the aviation marketplace. DPHM derived cost benefits to the operator of an aircraft may result in reduced revenue streams for the Original Equipment Manufacturer (OEM) or parts supplier. This document will address market drivers from the perspective of the end-user of an aircraft.

The primary market drivers for DPHM systems and technologies are much the same as for any other domain excepting that safety of flight and its attendant regulations pose additional challenges. The key market drivers discussed in this document are summarized below and discussed in more detail following:

• Cost of acquisition and ownership;

• Reliability and availability; and

• Airworthiness/flight-safety standards.

3.2.1 Cost of Ownership DPHM technologies can impact significantly on both acquisition and operating costs. It is not the intent of this document to discuss each perspective in an exhaustive manner but rather to highlight how DPHM technologies can benefit an aircraft owner/operator.

Decreased acquisition costs – DPHM technologies are intended to quickly and efficiently identify failures, both actual and impending, to the lowest feasible assembly level and to enable the effective planning of maintenance tasks. The result is reduced spares procurement at program initiation and even in a reduction in the overall number of aircraft or spares required due to increased availability and decreased attrition. If one can more reliably identify a faulted component on the first fault diagnostic attempt then the number of serviceable components incorrectly removed due to mis-diagnosis and the number of initial spares required will be reduced as will the numbers of spares required to support the pipeline between operations and overhaul facilities. Various studies have identified unsubstantiated parts removals as being 30-50% of all components removed. The magnitude of benefits becomes apparent when these components are items such as very high cost fuel control units.

Decreased costs of operation – The reduction of no-fault-found component removals has just been discussed however this factor will have a very real effect on the maintenance burden

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throughout the life of an aircraft system from maintenance labour, facilities and ancillary damage perspectives. If a component failure is incorrectly diagnosed one or many times, that clearly represents an increased requirement for maintenance human resources as well as facilities. To illustrate the magnitude of savings possible, the JSF program has targeted a 40% reduction in maintenance personnel required to support this aircraft. This factor accelerates as aircraft become evermore self-diagnostic with effective supply chain integration.

A related factor that often is not considered is the wear that occurs as a result of multiple repair attempts. Not only are components damaged as a result of un-necessarily replacement but additional wear and costs are incurred if flight testing is required prior to the return of an aircraft to revenue generating or military operations.

Opportunistic Maintenance – Increasing prognostic functionality, the identification of precisely when faults will occur or when performance will be unacceptably degraded, will enable increased opportunistic maintenance planning. DPHM will enable fault recovery to be undertaken when it is most cost-effective in terms of operational scheduling, facility location, and human resource availability.

Reduced warranty charges back to OEM – The complex supply chain and sometimes differing business objectives complicate the DPHM technology environment and highlight an area where benefits to one stakeholder may adversely impact another component of the supply chain. The example may be taken from an independent third party repair center whose diagnostic capabilities do not enable highly discriminating fault isolation and rectification. The resulting removal and replacement of a higher order assembly under warranty can benefit the repair center and owner/operator, while adversely impacting the supplier of component or pay-per-hour services supplier. Improved diagnostics, prognostics and enhanced supply chain integration will lessen the frequency and cost of unnecessary component replacement.

Supply chain integration – Current systems focus is on the identification of a faulted component. Once that step in the process is completed, the requirement for replacements parts is typically handed off to another organizational functional group. One objective of on-board self-diagnostic capability is that the fault, or incipient fault, knowledge be integrated with the supply chain process in aircraft fitted with advanced DPHM systems. In these systems, when a fault is detected in-flight, that information will be communicated to the logistics support organization who can have the required repair component awaiting the aircraft when it lands or on its way to the most appropriate repair center. Alternatively, if the part cannot be made available at the scheduled destination, that information can be passed to a scheduler/mission planner who can then decide whether to divert the aircraft, schedule a parts shipment or make arrangements for alternate aircraft.

Again to use a JSF metric, with the full implementation of the JSF PHM and Autonomic Logistics the US DoD is forecasting a logistics footprint decrease of 50% as compared to that of current fighters.

3.2.2 Reliability and Availability Better first time fixes, less time awaiting spares supply and other factors mentioned earlier increase aircraft availability. The issue of increased reliability is also beneficially affected by DPHM technologies due to fewer unexpected failures that can result in gate delays, cancellations and partial mission aborts or re-routing. These factors have been well described in preceding paragraphs. Advanced DPHM systems functionality will further improve aircraft reliability and availability through intelligent mission planning and scheduling where aircraft failures occur less often, or when faults can be either accepted without unacceptable flight safety degradation, or accommodated by redundant systems or software.

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Again to use a JSF PHM metric, the US DoD expects an improvement in sortie generation rate of 25% resulting from advanced PHM and Autonomic Logistics systems implementation. From a simplistic perspective, the increased reliability/availability derived from these advanced systems could effectively reduce military aircraft inventory requirements by 25%, a significant cost avoidance for the owner/operator.

3.2.3 Airworthiness It must be remembered that in the first two decade of the 21st century the world commercial aircraft fleet is expected to more than double in terms of aircraft hulls 16,000 to 34,000 (Boeing CMO 2004), and that Revenue Passenger Kilometres (RPK) will almost triple from 3.165 Trillion in 2002 to 8.4 Trillion in 2022 (Source Airbus GMF 2003). Thus, if the world aircraft operators simply maintain the current and demanding airworthiness performance standards, there will still be three times the hull losses that are currently experienced. Regardless of the absolute safety measures, an increased number of highly visible aircraft losses could reach a perceptual level that will adversely affect passenger mode-of-travel preferences away from air. Thus Airworthiness standards must not just be maintained but rather must be significantly improved. DPHM concepts and systems will be key factors in achieving improved airworthiness levels.

Increasing knowledge concerning the rate and level of damage accumulation in flight critical components coupled with increased life remaining analysis capability will ideally preclude an ever increasing number of catastrophic airborne failures or incidents causing passenger discomfort. This factor is perhaps the most obvious benefit of increasing DPHM functionality particularly as that functionality is implemented in on-board real time systems.

A component of improved flight safety arising from advanced DPHM systems concerns the amount and type of information that is provided to flight and ground personnel as a critical event unfolds. DPHM systems typically monitor a large number of sensors and store large quantities of both raw and processed data. Often times in the past, aircrew have been inundated with data that is not important to the resolution of an airborne emergency and the value of the data can be questioned if confusion has resulted. As the systems monitored increase in number and complexity it will be necessary to ensure that only the necessary information is provided to the flight crew and that decision aids are available for selecting optimal corrective responses. DPHM functionality in the future will increasingly offer the flight crew with options analysis/decision aids functionality and employ redundant systems or processes automatically. The functionality available in fly-by-wire systems today is an example of how alternate control surfaces can be applied to achieve less damaging structural loads or compensate for other failed or damaged control systems.

The US DoD VAATE program envisages aero-propulsion systems that can for example, identify the onset of aerodynamic instability within a gas turbine compressor and self-control the engine out of that damaging or potentially catastrophic operating state. This principle can be extended to situations where the engine can select less damaging matching conditions or more fuel efficient operating states. Similar examples can be found on the aircraft structure where control surfaces experiencing flutter type instability can be moved out of the excitation envelope and the required aircraft control input automatically addressed by other control surfaces.

3.3 Market Constraints While the benefits of DPHM can be significant, the costs of implementing DPHM sensors can also be significant and must not be overlooked in the cost and benefit analysis. Advanced DPHM sensors can be expensive to design-in, acquire, and support in operational environments that are the harshest imaginable.

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Another caveat on DPHM systems integration relates to false alarms that can have adverse program impact if improperly implemented. The response to this latter challenge lies in a thorough design, analysis, test and evaluation program prior to DPHM implementation. These false alarms are most significant when they result in pilot responses that are unsafe and have even been known to cause the loss of aircraft, as when helicopters have performed emergency water landings and then tipped over and sunk.

A human factor impacted by DPHM technologies relates to when a complex and reliable airplane experiences an un-expected fault. If the maintenance personnel have little experience troubleshooting the aircraft and little historical fault knowledge, a relatively minor fault can result in extended out-of-service periods.

In essence, the market constraints not surprisingly mirror the market drivers as:

• Cost of acquisition, implementation and ownership – of the DPHM systems;

• Reliability and availability of the DPHM systems and their output; and

• Airworthiness/flight-safety standards can not be adversely affected by the fitment of DPHM system, this self-evident concept has been overlooked in the past when unproved technology implementations occurred too early.

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4 System Requirements

4.1 Systems Requirement Overview In a previous Technology Insight Document devoted to Aero-propulsion systems the following system conceptual diagram was used to illustrate system components and performance domains.

Figure 2 – Representative DPHM System Block Diagram - JSF

During the DPHM Workshop held in Ottawa on November 18th, 2004, Mr Mike Augustin presented the very comprehensive overview of DPHM systems based on rotorcraft design considerations which is presented as Figure 3 on the following page.

Integrated Maintenance and

Logistics database

Aircraft/ Flight Envelope

Utility Systems

Vehicle Systems

Structures

Engine Sensors

-Vibration

-Temperature

-Pressure

-Speed

-Gas path debris

-Oil debris

-Tip Clearances

Ai rcraf t

Databuse

Air Vehicle Reasoner

Utility Sys Reasoner

Veh Sys Reasoner

Structures Reasoner

Engine Reasoner

-Signal processing

-Data validation

-Feature Extraction

-Data Fusion

On-Board Systems Ground based

Aircraft to Data downloader/system

Flight Crew Advisories In-flight Aircraft to ground communications link

Ground based maintenance analysis

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Figure 3 – Representative DPHM System Block Diagram – Rotorcraft (M. Augustin, Bell Helicopters, November 18th, 2004)

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4.2 System Requirements Map During the Aircraft Systems workshop held in Ottawa on 18 November 2004, each breakout session was requested to identify systems requirements that were of greatest importance to each aircraft sub-system group. The Results of the Aircraft Structures/airframe and Systems Integration breakout sessions are included in Table 1 below. Please note that the Aeropropulsion systems requirements listing in the left column of Table 1 is taken from the earlier Aeropropulsion and Aircraft Mechanical Systems DPHM TID Version .0.3 dated 19 Mar 04. Also please note that a detailed Anciliary Systems DPHM System Requirements document is being generated and will be distributed to participants as appropriate.

Table 1 – Aircraft Systems DPHM Systems Requirements Map

*Aeropropulsion Structures/ Airframe Systems Interation/ Health Management

Data Collection and Communication Crack detection Monitoring Need DPHM to control/predict cost

DiagnosticsEnvironmental monitoring (corrosion, Temp, Load)

Requires integration- Full and smart integration- Easy access to data, central data source

Fault Detection Strain monitoring Availability/reliability (push back cost)

Fault Isolation Vibration Planned environment (no surprises!)

Prognostics Accessibility/embedded sensorsPaperless/Electronic Signature (no manual data entry)

Failure Mode, Effects and Criticality Analysis (FMECA) Pressures/G-forces (acceleration)

Certification process for new technology

Component Life Tracking External noise – ground fire Integration of standardsLife Remaining Analysis GAG cycle Emissions mitigationPerformance Trending Torque variations Obsolescence AvoidanceFault Prediction Certification Feedback Loop

Health Management Flight hours

Need to take into account user inputs as early as possible- Commercial- Military- Other

Fault Assessment

In-flight and on-board information/data integration- Maintenance history- Intelligent management of data

Fault ReportingMaterials/design data- Fault progression model

Supply Chain Integration Active excitation for fault detection/isolation

Fault AccommodationSensitivity to anomaly detection – flight durationKnowledge of residual stressesLifing modelsFuture loads & environmental prediction/projectionKnowledge of failure modes & effects (FMECA)Integration of M&S capabilitySensor reliability & sensitivity

System engineering approach top design

Aircraft Systems Diagnostics, Prognostics and Health Management Systems Requirements Map (*Based on DPHM Workshop, Ottawa, 18 November 2004)

* Note- Aeropropulsion Systems Requirements taken from Aeropropulsion and Aircraft Mechanical Systems DPHM Technology Insight Document Version .3 19 Mar 04

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5 DPHM Technologies

Aeropropulsion Structures/ Airframe Systems Interation/ Health Management

Low Cycle Fatigue Monitor Antennae and RF communications Cognitive science – human factors processing of information

Acquisition, Reasoning, Predict

High Cycle Fatigue Monitor Correlation of operational data – fleet Common data format/dictionary Adaptive learning technology

Thermal fatigue Monitoring Damage modeling Data fusion Automated Data Mining

Creep monitoring Data mining Detection methodology Complete configuration control (as built and as maintained)

Crack detection and Monitoring Deterioration Modeling Expert systems – Reasoners: Case based, model based

Compliance with documentation standards

Micro-electromechanical systems (MEMS)

Emissions – Life performance trade-offs Interface with ASIP management Cost/Analysis methodology

Oil Debris Monitoring Expert system/ Knowledge capture M&S – Multi-scale, onboard/off board Data cleaning, data quality (raw data level), validation, missing data

Magnetic Plug Failure Characterization Optical - sensors, data transmission Human interaction (MANPRINT)SOAP Failure detection Reference data available on A/C Knowledge Base and data captureElectrostatic Debris Monitoring Failure prediction Reliability – Sensors and data Physics-based models

Patch Analysis Fault analysis, detection and isolation Rotary wing flight maneuver Real-time transmission of the data

Ferrography Fire detection – micro sensors Sensors, low cost, embeddable, corrosion, fatigue

Reuse of existing standards to enable technology (XML, data formats, …)

Gas Path Debris Monitoring FMEA development and interpretation Simplified models for real time processing Sensors and smart systems linked to failure odes

Inlet Debris Monitoring Generic failure, usage methods Structural modeling – Static/dynamicBaseline data

Wireless (related to sensors)

Exhaust Debris Monitoring Installation/ reliability Wireless technology and telemetry- Interference / EW- Reliability

IR Thermography Knowledge and process capture

Vibration Analysis Life cycle data analysisBlades/Airfoils Life Performance trade-offsEngine Maintenance credit certification

Gearbox Misassembly identificationRotor Track and Balance Operational data gatheringPhysical Alignment and Clearances

Overall system cost models

Seal leaks Pattern RecognitionShaft Alignment Power supplyAero-thermo Performance Assessment

RF systems, EMI, reliability

Thrust/Power assurance Software standardsControl System Malfunctions System architecture (ground/ air)Tip clearances Temperature, pressure, Velocity/flow,

debris, gas particulates, vibrationAirflow Test planningDecision Aids Wireless sensorsKnowledge Discovery and Data Mining (KDD)Model Based ReasoningData FusionIntegrated Assistant EnvironmentCase Base ReasoningHybrid ReasonersHealth ManagementAsset managementSchedulersCommunicationsDataloadersCompetency assessment and on-time delivery of trainingCall Home

Aircraft Systems Diagnostics, Prognostics and Health Management Technologies Map (Based on DPHM Workshop, Ottawa, 18 November 2004)

Technology List from Aeropropulsion and Aircraft

Mechanical Systems DPHM TID Version O.3 19 Mar 04

Table 2, the Aircraft Systems DPHM Technologies map was developed primarily during the Aircraft DPHM Workshop held in Ottawa on November 18th, 2004. The left column of Table 2 was however taken from the original Aeropropulsion and Aircraft Mechanical Systems DPHM TID Version 0.3 dated 19 March, 2004. This information is included for comparative purposes and the reader will note that in the original DPHM TID, an attempt was made to categorize technologies as being diagnostics, prognostics or health management focused. Narrative descriptions of each of the Aeropropulsion DPHM technologies listed in the left column are included in the original DPHM TID.

Table 2 – Aircraft Systems DPHM Technologies Map

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6 Canadian DPHM Capabilities and Gaps {This section of the Technology Insight Document will be populated following future DPHM workshops and for a.}

6.1 Market Focus

6.1.1 Military Aircraft

6.1.2 Commercial Aircraft

6.1.3 Regional Aircraft

6.2 DPHM Capabilities

6.2.1 Military Aircraft

6.2.2 Commercial Aircraft

6.2.3 Regional Aircraft

6.3 Canadian DPHM Gap Assessment

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7 Technology Implementation Opportunities A considerable amount of support and enthusiasm was expressed by a large community of industrial, academic and government agencies for pursuing DPHM technology insertion or demonstration projects. General consensus was reached that a Standing Working Group be established to provide a communication mechanism for continued improvements in Canadian competitiveness. The draft Terms of Reference for a standing working group have been developed and discussed and further activity is anticipated. This will be the first of the technology implementation opportunities discussed in this section.

Most significantly however, was the fact that a total of 16 potential DPHM projects were identified, outlined and discussed at the second DPHM workshop held in Ottawa on November 18th, 2004. These projects are summarized in Section 7.2 and discussed individually in subsequent paragraphs.

7.1 DPHM Working Group The primary objective of the DPHM Standing Working Group is to develop and implement a structured approach for continuing consideration of DPHM programs and issues from a Canadian Aerospace sector perspective. Examples of activities that will be pursued include the following activities, although many more will be identified as the working group is established and begins deliberations:

• Develop needs and gap analysis;

• Initiate and organize technical fora; and

• Enable a communication mechanism, both nationally and internationally.

The first step in the formation of the DPHM Working Group would be the establishment of a Steering Committee whose role would be to build the business model for the broader working group. A proposed Terms of Reference for this Steering Group is provided in Annex C of this document.

7.2 Technology Demonstration Projects Overview Prior to and during the DPHM Workshops conducted as part of the DPHM TIRM, a total of 16 technology demonstration or insertion projects were tabled and discussed. Table 3 below provides a summary of these projects and for each project identifies: the company that generated the project outline, the project title, objectives, and anticipated output. Each project is then discussed in somewhat more detail in subsequent subparagraphs. The intent of this section is to provide a top level summary of the projects and capture any workshop discussion points for each project.

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Table 3 – DPHM Technology Insertion Project Summary Table

DPHM Technology Insertion Project Summary Table

Company Project Title Objective Output

BHTI1 - Bell Helicopters

Individual Aircraft Usage Monitoring

Define a low cost Usage Monitoring System that could be certifiable for a new helicopter model

System Requirements Document and a User Interface ICD

BHTI2 - Bell Helicopters

Development of Structures with Embedded Sensors

Develop embedded sensors, possibly wireless, that would support the newer Damage Tolerance Approach.

-System Requirements Document -prototype embedded sensor network

CB1 -CaseBank Technologies

FMEA/Field Diagnostic Interoperability

To link field experience and engineering analysis to provide both a better diagnostic tool and critical feedback on the design.

A methodology for extracting FMEA content into a practical field diagnostic tool, and for linking field experience back to design items.

CB2 -CaseBank Technologies

Interpretation of Trends and Multivariate Correlations

To semi-automate the expert analysis of data patterns resulting from DPHM methods.

A methodology for capturing and applying human expertise to the context-sensitive interpretation of trends and multivariate correlations.

HW - Honeywell

DPHM Requirements for Aircraft Subsystems

To understand and develop DPHM requirements at the utility subsystem level for DPHM development

DPHM requirements for each subsystem and at the aircraft level

NP1 -Neptec Development of a 3D Standoff Scanner for Aircraft NDI

Correlate aircraft corrosion damage with detectable surface pillowing.

A highly accurate 3D standoff NDI tool and method to detect sub-surface corrosion in aircraft assemblies.

NP2 -Neptec Develop a 3D Non-contact System for Measuring Airframe Deflections during Testing

Replace multiple displacement transducers and data acquisition systems with a 3D non-contact measurement system.

An accurate tool and method to provide real-time measurement and targetless tracking of airframe deflections while under test.

NP3 -Neptec Develop a Rapid 3D Non-contact System Capable of Reverse Engineering of As-Built and As-Repaired Aircraft

Provide solid models of as-built and/or as-repaired aircraft assemblies or structures using a 3D non-contact laser scanner.

A high speed 3D tool and method to provide traceability of as-built and/or as-repaired aircraft.

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DPHM Technology Insertion Project Summary Table

Company Project Title Objective Output

LPTI Prognosis and Emission Mitigation for DPHM Infrastructure

To develop a series of onboard prognosis and emission mitigation analytical tools with real operational data and physics based models for high accuracy/confidence

Companies working together to realize a complete life extension and emission mitigation system solution. Solid value to all stake holders

SAL -Standard Aero Limited

Develop and Demonstrate DPHM Benefits on Legacy Fleet

To develop and field DPHM technologies on the CF’s T56 fleet and demonstrate life cycle performance/cost improvements.

Companies working together to realize a complete customer support network for DPHM.

PWC1 - Pratt & Whitney Canada

Maintenance Intervention Planning

Establish benchmarking/ analysis techniques of DPHM data to 1) identify patterns of deterioration, 2) correlate with mission profile and wear/tear on hardware in order to predict next maintenance.

A methodology to leverage DPHM fleet data to derive timing and high level scope for maintenance interventions

PWC2 - Pratt & Whitney Canada

Maintainability Tracking and Rapid Maturing Process

To ensure DPHM data is routinely surveyed to (1) monitor the effectiveness of the programs (2) reduce the cycle time for detection of arising product improvement

A methodology for structuring and analyzing the DHPM data to correlate actual field data and development analytical model

PWC 3 -Pratt & Whitney Canada

Test Results Monitoring and Diagnostics

Pool knowledge relative to troubleshooting practices and identification of remedial action to engine test rejects at maintenance facilities. Incorporate into a system for tracking and diagnostic of test rejects.

A methodology for capturing and applying scattered human expertise. Feedback to improve product and processes use for maintenance and facilities turn time.

PWC4 - Pratt & Whitney Canada

Micro-electromechanical (MEMS)Systems for Fire Detection

To develop new micro sensors based on combined heat and carbon monoxide gas detection for non-intrusive, lightweight and reliable fire safety systems

New micro sensor technology compatible with engine and aircraft fire detection systems

PWC5 - Pratt & Whitney Canada

Mobile Phone Engine Data Transfer

Wireless engine data transfer to local mobile phone network, from static aircraft on ground, using engine internal antennas invisible to aircraft .

Optimized mobile phone antenna locations and 3D RF modeling of aircraft / engine structure will provide framework for wireless data transfer system design rules

PWC6 - Pratt & Whitney Canada

Wireless new engine sensors

To enable new DPHM methods using engine core control sensors, wireless, and operating in harsh gas turbine environment

RF systems development for wireless sensors, prototype RF micro-antennas integrated to engines

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7.3 BHTI1 - Individual Aircraft Usage Monitoring Project Title: Individual Aircraft Usage Monitoring

Company Proponent Bell Helicopters Textron International

Proponent Point of Contact Bob Fews, Bell Helicopter Canada Mike Augustin, Bell Helicopter Fort Worth, Tx

Challenges

One of the “hard savings” associated with Health and Usage Monitoring Systems lies in the Usage area but these applications have not been certified on helicopters to-date.

Objectives

Define a low cost Usage Monitoring System that could be certifiable for a new helicopter model

DPHM Domains Aircraft and Fleet Level

Outputs

System Requirements Document and a User Interface ICD

Collaborators

Bell, DND, NRC

Synergy with other projects

Estimated schedule duration 12-24 Months

Estimated funding required $800K

Technology Readiness Level

Benefits

DOC Reduction, Safety, Life extension

Risks

Validation

Comments

Revision date

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7.4 BHTI2 - Development of Structures with Embedded Sensors Project Title: Development of Structures with Embedded Sensors

Company Proponent Bell Helicopters Textron International

Proponent Point of Contact Bob Fews, Bell Helicopter Canada Mike Augustin, Bell Helicopter Fort Worth, Tx

Challenges

The Rotorcraft Industry is changing from a “Safe Life” airworthiness approach to what is known as the “Damage Tolerance” methodology

Objectives

Develop embedded sensors, possibly wireless, that would support the newer Damage Tolerance Approach.

DPHM Domains Aircraft Structural Components and Fleet Level Monitoring methods.

Outputs

System Requirements Document; prototype embedded sensor network

Collaborators

Sensor or Subsystem supplier(s) Bell, DND, NRC

Synergy with other projects PWC6

Estimated schedule duration 18-24 Months

Estimated funding required $900K

Technology Readiness Level

Benefits

Enabling damage tolerance

Risks

Reliability, Durability

Comments

Revision date

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7.5 CB1 - FMEA/Field Diagnostic Interoperability Project Title: FMEA/Field Diagnostic Interoperability

Company Proponent CaseBank Technologies Inc

Proponent Point of Contact Phil D’Eon, [email protected]

Challenges

Field (end-user) experience often differs from that anticipated through design analysis, leading to less-than-optimal diagnostics.

Objectives

To link field experience and engineering analysis to provide both a better diagnostic tool and critical feedback on the design.

DPHM Domains Any of: engine, APU, avionics, electrical, or other of similar complex nature

Outputs

A methodology for extracting FMEA content into a practical field diagnostic tool, and for linking field experience back to design items.

Collaborators

Tier 1 OEM, or Tier 2 Systems Integrator NRC, LPTi

Synergy with other projects

Estimated schedule duration 12-18 months.

Estimated funding required

Technology Readiness Level 3

Benefits

Interoperability, potential for validating FMEA, structured way of capturing knowledge, low-cost alternative to FIM, feedback to FIM

Risks

Reliability of FMEA, data availability and cost, buy-in from end users?

Comments

CaseBank has demonstrated initial feasibility concepts. The demonstrator environment exists that utilizes case-based reasoning. A technical proposal exists.

Revision date

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7.6 CB2 - Interpretation of Trends and Multivariate Correlations Project Title: Interpretation of Trends and Multivariate Correlations

Company Proponent CaseBank Technologies Inc

Proponent Point of Contact Phill D’Eon, [email protected]

Challenges

Sensor-based DPHM systems can reveal events, trends, and parameter correlations of interest, but the meaning can be ambiguous as to internal or external causes, and therefore often requires interpretation by human experts.

Objectives

To semi-automate the expert analysis of data patterns resulting from DPHM methods.

DPHM Domains Any of: engine, APU, test cell, or other applications where sensor data is trended and/or correlated

Outputs

A methodology for capturing and applying human expertise to the context-sensitive interpretation of trends and multivariate correlations.

Collaborators

Tier 1 OEM, or Tier 2 Systems Integrator PWC

Synergy with other projects PWC3

Estimated schedule duration 12-18 Months

Estimated funding required

Technology Readiness Level

Benefits

Capture and dissemination of experience, augment throughput, early warning, increased effectiveness of the DPHM process, increased availability, decreased LC and op costs

Risks

Complacency (increase dependency on technologies), effects of bad data, potential for reduction in # of experts

Comments

CaseBank has demonstrated initial concept feasibility but requires an integrated system environment to demonstrate full strategic potential

Revision date

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7.7 HW - DPHM Requirements for Aircraft Subsystems Project Title: DPHM Requirements for Aircraft Subsystems

Company Proponent Honeywell

Proponent Point of Contact Jean Menard – Team Leader – Bombardier L. Otupiri – TPC, ChunShen Yang - NRC, Dr. W.Dmochowski - NRC, Chun Ho Lam - Honeywell

Challenges

To balance supplier DPHM development cost vs. DPHM effectiveness expectation

Objectives

To understand and develop DPHM requirements at the utility subsystem level for DPHM development

DPHM Domains Aircraft utility subsystems, (e.g. APU, Electric Power Systems, Environmental Controls System, etc.)

Outputs

DPHM requirements for each subsystem and at the aircraft level

Collaborators

Lead Company: Bombardier, Participants: Companies capable of supplying aircraft subsystems and DPHM technologies(e.g., engine, APU, etc.), Gov. Lab and Universities

Synergy with other projects

Estimated schedule duration 12 Months, beginning Dec 2004

Estimated funding required

Technology Readiness Level

Benefits

Risks

Comments

This will assist the design and implementation for off board and on board DPHM systems and methodologies. Encourage cooperative and better definition for effort among suppliers, Government Lab. and University.

Revision date

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7.8 NP1 - Development of a 3D Standoff Scanner for Aircraft NDI Project Title: Development of a 3D Standoff Scanner for Aircraft NDI

Company Proponent Neptec Design Group

Proponent Point of Contact Philip Church [email protected] Iain Christie, [email protected]

Challenges

Design and build a 3D standoff system capable of detecting corrosion damage in aircraft skin-stringer panels by measuring surface ‘pillowing’.

Objectives

Correlate aircraft corrosion damage with detectable surface pillowing.

DPHM Domains Airframe structures; fuselage, wings, vertical and horizontal stabilizers.

Outputs

A highly accurate 3D standoff NDI tool and method to detect sub-surface corrosion in aircraft assemblies.

Collaborators

IAR-NRC, Aircraft maintenance and inspection service providers. Neptec, DND, NRC

Synergy with other projects

Estimated schedule duration Start ASAP, duration 12 -18 months.

Estimated funding required $150K

Technology Readiness Level

Benefits

Safety, Cost/time saving, Improved reliability/availability

Risks

High Cost

Comments

Neptec has a successful history in developing laser vision systems, most recent 3D non-contact system will be used for damage detection on the Space Shuttle.

Revision date

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7.9 NP2 - Develop a 3D Non-contact System for Measuring Airframe Deflections during Testing

Project Title: Develop a 3D Non-contact System for Measuring Airframe Deflections during Testing

Company Proponent Neptec Design Group

Proponent Point of Contact Philip Church [email protected] Iain Christie, [email protected]

Challenges

Design and build a 3D non-contact system capable of measuring and tracking airframe deflections during testing. Targets on the test structure are not required.

Objectives

Replace multiple displacement transducers and data acquisition systems with a 3D non-contact measurement system.

DPHM Domains Airframe structures; fuselage, wings, vertical and horizontal stabilizers.

Outputs

An accurate tool and method to provide real-time measurement and targetless tracking of airframe deflections while under test.

Collaborators

IAR-NRC, Aircraft manufacturers and test centers. Neptec, DND, NRC

Synergy with other projects

Estimated schedule duration Start ASAP, duration 12 -18 months.

Estimated funding required $300K

Technology Readiness Level

Benefits

Reduced costs

Risks

Dynamic limitations

Comments

Neptec has a successful history in developing laser vision systems, most recent 3D non-contact system will be used for damage detection on the Space Shuttle.

Revision date

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7.10 NP3 - Develop a Rapid 3D Non-contact System Capable of Reverse Engineering of As-Built and As-Repaired Aircraft

Project Title: Develop a Rapid 3D Non-contact System Capable of Reverse Engineering of As-Built and As-Repaired Aircraft

Company Proponent Neptec Design Group

Proponent Point of Contact Philip Church [email protected] Iain Christie, [email protected]

Challenges

Design and build a rapid 3D non-contact system capable of accurate reverse engineering capabilities.

Objectives

Provide solid models of as-built and/or as-repaired aircraft assemblies or structures using a 3D non-contact laser scanner.

DPHM Domains Airframe assemblies and sub-assemblies

Outputs

A high speed 3D tool and method to provide traceability of as-built and/or as-repaired aircraft.

Collaborators

IAR-NRC, aircraft manufacturers, MOD lines, aircraft interior manufactures and installation centers, repair centers. Neptec, DND, NRC

Synergy with other projects

Estimated schedule duration Start ASAP, duration 12 -18 months.

Estimated funding required

Technology Readiness Level

Benefits

Reduced costs

Risks

Dynamic limitations

Comments

Neptec has a successful history in developing laser vision systems, most recent 3D non-contact system will be used for damage detection on the Space Shuttle.

Revision date

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7.11 LPTI - Prognosis and Emission Mitigation for DPHM Infrastructure Project Title: Prognosis and Emission Mitigation for DPHM Infrastructure

Company Proponent Life Prediction Technologies Inc.

Proponent Point of Contact Bharat Ghader [email protected] Ashok Koul [email protected]

Challenges

Aerospace and Industrial fleet operators faced with Increasing life cycle costs & environmental impacts of GHG emissions

Objectives

To develop a series of onboard prognosis and emission mitigation analytical tools with real operational data and physics based models for high accuracy/confidence

DPHM Domains Prognosis – Increase life of engine and critical components, minimize number of spares required and reduce labor costs. Emission mitigation – structural integrity based.

Outputs

Companies working together to realize a complete life extension and emission mitigation system solution. Solid value to all stake holders

Collaborators

Aerospace and Industrial Fleet operators, system Integrators, data management companies, other engineering specialty organizations, MRO facilities, Field service organizations (MRO, FBOs, airlines, etc) & OEM. PWC

Synergy with other projects PWC1

Estimated schedule duration Expected duration 12-24 months.

Estimated funding required

Technology Readiness Level

Benefits

Real-time data acquisition, enhanced part management, fine grained continuous assessment – safety, legacy fleets

Risks

Potential regulation issues, depends on data completeness, reliability, integrity, potential longer use of components – potential effects on safety?

Comments

Life Prediction has developed new and innovative knowledge based prognosis customer solutions for 3+ in collaboration with universities, NRC & DND. Our expert system is now ready to be included in a larger DPHM framework and infrastructure.

Revision date

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7.12 SAL - Develop and Demonstrate DPHM Benefits on Legacy Fleet Project Title: Develop and Demonstrate DPHM Benefits on Legacy Fleet

Company Proponent Standard Aero Ltd

Proponent Point of Contact [email protected]

Challenges

Develop a DPHM structure for a legacy fleet that generates incremental profit for companies and performance/financial savings for the customer.

Objectives

To develop and field DPHM technologies on the CF’s T56 fleet and demonstrate life cycle performance/cost improvements.

DPHM Domains Focused on T56 engine. However, infrastructure, algorithms etc are to be applicable to all engine types including APUs.

Outputs

Companies working together to realize a complete customer support network for DPHM.

Collaborators

Lead Company: Standard Aero Ltd. Participants: Major subsystem manufacturers, Data management companies, engineering specialty organizations, MRO facilities, and Field service organizations (MRO, FBOs, airlines, etc)

Synergy with other projects

Estimated schedule duration Expected duration 36 - 48 months.

Estimated funding required

Technology Readiness Level

Benefits

Good framework for collaborative work, clear application, goal oriented (profitability), applicable to other fleets

Risks

What happens if not profitable, duplication of OEM data, potential certification/ implementation/ regulatory issues, only engine, system integration

Comments

Standard Aero is driving toward new and innovative customer solutions, but there is an industry gap in being able to implement cost effective solutions in the field that meet a wide range of individual customer requirements.

Revision date

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7.13 PWC1 - Maintenance Intervention Planning Project Title: Maintenance Intervention Planning

Company Proponent Pratt and Whitney Canada Corp.

Proponent Point of Contact [email protected]

Challenges

Large amount of DPHM data is captured, resulting in need for tools to mine/analyze this data efficiently and get full benefit in a timely manner.

Objectives

Establish benchmarking/ analysis techniques of DPHM data to 1) identify patterns of deterioration, 2) correlate with mission profile and wear/tear on hardware in order to predict next maintenance.

DPHM Domains Any of: airframer, engine, APU or other of similar complex nature where DPHM data is collected

Outputs

A methodology to leverage DPHM fleet data to derive timing and high level scope for maintenance interventions

Collaborators

Major subsystem manufacturers, Data management companies, MRO facilities PWC, LPTi, DND NRC, Globv

Synergy with other projects LPTI

Estimated schedule duration Expected duration 12-18 months.

Estimated funding required

Technology Readiness Level 3-5

Benefits

Shop load leveling, enhanced part management, availability / JIT, increased safety

Risks

Reduce component life, false alarms, feasibility / faith

Comments

P&WC has demonstrated initial concept feasibility but requires an integrated system environment to demonstrate full strategic potential.

Revision date

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7.14 PWC2 - Maintainability Tracking and Rapid Maturing Process Project Title: Maintainability Tracking and Rapid Maturing Process

Company Proponent Pratt and Whitney Corp.

Proponent Point of Contact [email protected]

Challenges

The knowledge potential derived from DPHM data is not fully exploited. Tasks such as maintainability analysis (e.g.MSG3) are not systematically subject to validation after product have entered service.

Objectives

To ensure DPHM data is routinely surveyed to (1) monitor the effectiveness of the programs (2) reduce the cycle time for detection of arising product improvement

DPHM Domains Any of: aircraft, engine, APU or other applications where DPHM data are collected

Outputs

A methodology for structuring and analyzing the DHPM data to correlate actual field data and development analytical model.

Collaborators

Major subsystem manufacturers, service organizations (FBOs, MROs, airlines..), data management companies PWC, DND NRC, Globv

Synergy with other projects Similar risks and benefits to CB1

Estimated schedule duration Expected duration 18-24 months.

Estimated funding required

Technology Readiness Level 1

Benefits

Elimination of campaigns

Risks

No MRO return

Comments

P&WC has demonstrated the effectiveness of its diagnostics and prognostics tools (e.g. WebECTM®) for their engines. This project is to expand its capability in predicting shifts in maintenance scope and burden.

Revision date

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7.15 PWC3 - Test Results Monitoring and Diagnostics Project Title: Test Results Monitoring and Diagnostics

Company Proponent Pratt and Whitney Corp.

Proponent Point of Contact [email protected]

Challenges

Modern Test-cell equipment data acquisition systems enable DPHM applications such as trending and diagnostics. Interpretation of results is typically not well documented and impairs the efficiency of such applications.

Objectives

Pool knowledge relative to troubleshooting practices and identification of remedial action to engine test rejects at maintenance facilities. Incorporate into a system for tracking and diagnostic of test rejects.

DPHM Domains Any of: aircraft, engine, APU or other applications test equipment with capability to collect DPHM data.

Outputs

A methodology for capturing and applying scattered human expertise. Feedback to improve product and processes use for maintenance and facilities turn time.

Collaborators

Test equipment manufacturers/integrators, service organizations (FBOs, MROs, airlines..), data management companies PWC, CaseBank, MDS, DND, NRC, Globv

Synergy with other projects CB2

Estimated schedule duration Expected duration 12-18 months.

Estimated funding required

Technology Readiness Level 1-2

Benefits

Consistency, fewer test failures, close loop - work scope (better use of experience

Risks

Willingness of MROs to share data (competitive advantage), data sharing issues (taxonomy, format, incompatibilities)

Comments

Revision date

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7.16 PWC4 - Micro-electromechanical (MEMS)Systems for Fire Detection

Project Title: Micro-electromechanical (MEMS)Systems for Fire Detection

Company Proponent Pratt Whitney Canada Corp.

Proponent Point of Contact [email protected]

Challenges

Conventional aircraft/engine fire detection rely on intrusive heat wire arrays or smoke detectors with average performance.

Objectives

To develop new micro sensors based on combined heat and carbon monoxide gas detection for non-intrusive, lightweight and reliable fire safety systems

DPHM Domains Any of: aircraft, engine, APU, test cell, or other applications where fire sensor data is collected.

Outputs

New micro sensor technology compatible with engine and aircraft fire detection systems

Collaborators

Major subsystem manufacturer , Canadian University, collaboration with NASA JPL Concordia, ETS, EP

Synergy with other projects

Estimated schedule duration Expected duration 24-36 months.

Estimated funding required

Technology Readiness Level 1

Benefits

Risks

Comments

Development of fire detection MEMS sensors follows advanced DPHM chemical sensor research by Makel Engineering (USA) and EADS (Germany), as presented at CANEUS Nov2004 Conference.

Revision date

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7.17 PWC5 - Mobile Phone Engine Data Transfer Project Title: Mobile Phone Engine Data Transfer

Company Proponent Pratt Whitney Canada Corp.

Proponent Point of Contact [email protected]

Challenges

Aero engine maintenance data is linked to aircraft data transfer systems that require wiring cables and/or airworthiness certification of aircraft antennas

Objectives

Wireless engine data transfer to local mobile phone network, from static aircraft on ground, using engine internal antennas invisible to aircraft .

DPHM Domains Engine, APU,

Outputs

Optimized mobile phone antenna locations and 3D RF modeling of aircraft / engine structure will provide framework for wireless data transfer system design rules.

Collaborators

Major subsystem manufacturer, Canadian University Concordia, ETS, EP

Synergy with other projects

Estimated schedule duration Expected duration 18-24 months.

Estimated funding required

Technology Readiness Level 3

Benefits

Risks

Comments

Canadian university already involved with preliminary work.

Revision date

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7.18 PWC6 - Wireless New Engine Sensors Project Title: Wireless New Engine Sensors

Company Proponent Pratt Whitney Canada Corp.

Proponent Point of Contact [email protected]

Challenges

Conventional DPHM engine control sensors rely on wired interfaces, thereby limiting sources of DPHM data.

Objectives

To enable new DPHM methods using engine core control sensors, wireless, and operating in harsh gas turbine environment

DPHM Domains Any of: engine, APU, test cell, or other applications where sensor data is collected.

Outputs

RF systems development for wireless sensors, prototype RF micro-antennas integrated to engines

Collaborators

Major subsystem manufacturer , Canadian University, collaboration with NASA JPL Concordia, Bell, EPS, EP

Synergy with other projects BHTI2

Estimated schedule duration Expected duration 24-36 months.

Estimated funding required

Technology Readiness Level 1

Benefits

Risks

Comments

Development of engine wireless sensors follows advanced DPHM vibration monitoring research by NASA JPL, as presented at CANEUS Nov2004 Conference.

Revision date

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8 Recommendations DPHM technologies are pervasive and of significant interest to the Canadian aerospace sector. This interest originates from both OEM and supplier segments. Additional and continuing effort is necessary to ensure that the competitiveness of Canadian participants is developed to the greatest extent possible. Based on the discussions of the two DPHM workshops held, a number of recommendations are offered:

• There is a requirement for continued focus and networking in this technology domain;

• The formation of a standing working group would benefit both government and industrial DPHM communities of interest through the organization of focused technology development and demonstration activities as well as the provision of effective communication mechanisms; and

• Technology demonstrator environments are considered a key mechanism for concept demonstration and validation. At present, there is no industry focused technology demonstrator program and consideration should be given to an appropriate framework within which effective co-investment could occur.

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9 Definitions Definitions and abbreviations are provided below which apply to this document.

Abbreviation Expanded Term or Meaning

A&D Aerospace and Defence

AAMS Aero-propulsion and Aircraft Mechanical Systems

AEDC US Air Force Arnold Engineering Development Center

AFD Acoustic FOD (Foreign Object Damage) Detector

AFRL Air Force Research Lab

AIAC Aerospace Industries Association of Canada

ANN Artificial Neural Network

AVRS Air Vehicle Research Section

AVT Applied Vehicle Technology

BVM8X Blade Vibration Meter

CA Criticality Analysis

CASE Canadian Aerospace Synthetic Environment

CBR Case-Based Reasoning

CO2 Carbon Dioxide

DND Department of national Defence (Canada)

DoD (US) Department of Defense

DPHM Diagnostics, Prognostics and Health Monitoring

DRDC Defence R&D Canada

EBM Electrostatic Bearing Monitor

ECS Eddy Current Blade Sensor

EDMS Engine Distress Monitoring System

EODM Electrostatic Oil Debris Monitor

EUCAMS Engine Usage and Condition Monitoring Systems

FCU Fuel Control Unit

FMEA Failure Mode and Effects Analysis

FMECA thorough Failure Mode, Effects and Criticality Analysis

FOD Foreign Object Damage

HCF High Cycle Fatigue

HUMS Health Usage and Monitoring

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Abbreviation Expanded Term or Meaning

IAR Institute for Aerospace Research

IDMS Ingested Debris Monitoring System

IETM Interactive Electronic Technical Manuals

IHPTET Integrated High Performance Turbine Engine Technology Program

IHUMS Integrated Health and Usage Monitoring Systems

IIT Institute for Information Technology

IR Infrared

JSF Joint Strike Fighter

KDD Knowledge Discovery and Data Mining

LCF Low Cycle Fatigue

MBR Model Based Reasoning

MEMS Micro-Electro Mechanical Systems

NATO North Atlantic Treaty Organization

NAWCAD Naval Air Warfare Center Aircraft Division

NOX Nitrides of Oxygen

NRC National Research Council of Canada

OCM Oil Condition Monitor

OEM Original Equipment Manufacturer

PHM Prognostics and Health Management

PIWG Propulsion Instrumentation Working Group

PZT Piezoceramic Patch Crack Detection

RLI Robust Laser Inferometer

RTO Research and Technology Organization

SME Small to Medium Enterprise

SWAN Stress Wave Analysis

TID Technical Insight Document

TIRM Technology Insertion Roadmaps

USAF US Air Force

VA Vibration analysis

VAATE Versatile Affordable Advanced Turbine Engines

Vibes Vibration monitoring

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10 References 1. Technology Roadmapping – A Strategy for Success,

Cat. No. C2-538/2000E ISBN 0-662-29689-3 53294E http://strategis.ic.gc.ca/epic/internet/intrm-crt.nsf/vwGeneratedInterE/Home

2. Fundamentals of Technology Roadmapping

Strategic Business Development Department Sandia National Laboratories P.O. Box 5800 Albuquerque, NM 87185-1378 http://www.sandia.gov/Roadmap/home.htm#what01

3. Canadian Aircraft Design, Manufacturing and Overhaul Technology Road Map

(Ontario Pilot Project) November 1996 http://strategis.ic.gc.ca/epic/internet/intrm-crt.nsf/vwGeneratedInterE/h_rm00051e.html

4. Industry Canada Aerospace and Defence Technology Framework Version 4.0, September 10th, 2002;

5. Aeropropulsion and Aircraft Mechanical Systems Diagnostics, Prognostics and Health Management Technology Insight Document Version 0.3 dated 19 March 2004

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Annex A - Inventory of Relevant DPHM Activities

Program descriptions, summaries or website contents, are provided in summary form for DPHM relevant projects. Where available, this Annex also contains weblinks to DPHM relevant activities or websites where individual organizations provide a range of activities or programs having relevance to the DPHM Technology Insight Document and process.

Activity Title: American Helicopter Symposium

"New Frontiers in Vertical Flight" 61st Annual Forum & Technology Display Gaylord Texan Resort - Grapevine, TX June 1 - 3, 2005

Website: http://www.vtol.org/ahsfrm.html

Activity Description: Workshop with a number of technical sessions and one devoted to HUMS

Health and Usage Monitoring Technical Session

SESSION CHAIR: Michael Augustin, Bell Helicopter Textron, (817) 280-8719; FAX (817) 278-8719; [email protected]

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Activity Title: CANEUS 2004 Conference on Micro-Nano-Technologies for Aerospace Applications

Website: http://www.caneus.org/CANEUS04/program.htm

Activity Description: CANEUS 2004 is an international conference devoted to Micro-Nano-technology (MNT) development for Aerospace Applications held in Monterey, Monterey, California, November 1 - November 5, 2004

Concept papers presented at CANEUS 2004 were:

2004-A01 Development of Micro Attitude & Orbit Control Systems (µAOCS)

2004-A02 Reliability Testing of Micro-Sensors, Micro-Actuators and Micro-Switches

2004-A03 Effects of Space Radiation on MNT Devices

2004-A04 Nano/Pico-Satellite constellations for earth orbit or space exploration

2004-A05 Nano-composite Materials for Thermal Protection and Radiation Shielding Systems

2004-A06 Nanofiber Composite Materials for Load Bearing Structural Applications

2004-A07 Multifunctional Composite Materials with MNT Embedded Sensors

2004-A08 MNT based Space Transportation & Re-entry Technologies

2004-A09 Nanosensors and Devices

2004-A10 Nano-Optoelectronic Detectors and Lasers

2004-A11 MNT-based Sensors for Aircraft/Spacecraft Structural Health Monitoring

2004-A12 MNT-based Sensors for Astronaut Health Monitoring and Environmental Control

2004-A13 MNT for Miniaturized Scientific Instruments for Planetary Exploration

2004-A14 MNT Based Harsh Environment Sensors

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Activity Title: European 6th Framework

Website: http://europa.eu.int/comm/research/fp6/index_en.html

Two 6th Framework thematic areas were identified as having relevance to the DPHM Technology Insight document. They are briefly introduced below with website links identified for each of these thematic areas. Budget totals are also provided for these thematic areas. In view of the breadth and depth of these thematic areas, no attempt has been made to describe the activities and the reader is invited to access the websites as indicated for more detail.

Activity Title: Nanotechnologies and nanosciences, knowledge-based multi-functional materials and new production processes and devices

Website: http://europa.eu.int/comm/research/fp6/p3/index_en.html

Budget: 1,300M Euros

This is a multi-disciplinary thematic area that addresses a broad range of technologies and market sectors. As indicated in the title there three separate fields of endeavour included in this thematic area and they are:

• Nanotechnologies and nanosciences,

• Knowledge-based multi-functional materials and

• New production processes and devices

The objectives of this thematic theme are reproduced from the website identified above

• To help provide Europe with the critical mass of capacities to develop and exploit those high technologies at the basis of the products, services and production processes of the future, which are essentially knowledge based.

• To develop intelligent materials for applications in sectors such as transport, energy, electronics and biomedicine representing a potential market of several billion euro.

• To develop flexible, integrated and clean systems requiring a substantial research effort in the application of new production and management technologies.

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Activity Title: European 6th Framework

Website: http://europa.eu.int/comm/research/fp6/index_en.html

Activity Description: Aeronautics and Space

Website: http://europa.eu.int/comm/research/fp6/p4/index_en.html

Budget: 1,075M Euros

The objective of this thematic area is stated as being: To strengthen, by integrating its research efforts, the scientific and technological bases which underpin the competitiveness of the European aeronautics and space industry.

In the aeronautics portion of this thematic area the following three main areas are identified:

• Increased competitiveness of the European industry in terms of the production of civil aircraft, engines and equipment;

• Reduced environmental impact of aviation (fuel consumption, emissions of CO2 , NO X and other chemical pollutants, noise pollution);

• Increased capacity and safety of the air transport system, in support of a 'Single European Sky' (air traffic control and management systems);

Once again there are numerous calls for proposals and there is no intent here to provide a comprehensive assessment of activities under this 6th Framework Thematic Area.

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Activity Title: Canadian Department of National Defence and National Research Council – Future Offensive Vehicle Prognostics and Health Management Project

Contact: Head, Air Vehicle Research Section (H/AVRS), Mr. Ken McRae, Phone: 613-991-6908, email: [email protected]

Activity Description:

This is a 50/50 funded program involving two National Research Council Institutes, the Institute for Aerospace Research (IAR) and the Institute for Information Technology (IIT). Separate descriptions follow for the programs at each of these institutes.

The objectives of this project from a DND perspective are as follows:

• Identify, develop and demonstrate key DPHM technologies applicable to the CF and dual use systems

• Establish a process across DND to plan, champion and implement PHM

The activities planned between April 2004 and the end of March 2006 are as follows:

• Assess JSF core and PHM technologies (through in-depth evaluation with all relevant data)

• Assess effects of the new technologies on CF's procedures, methods, and systems.

• Disseminate results on JSF's PHM technologies through seminars and meetings with relevant CF staff

• Build an appropriate infrastructure to gather related documentation, software, and data

• Elaborate an R&D roadmap for the integration of the evolving technologies

• Write final project report and distribute it to relevant organizations

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Activity Title: Canadian Department of National Defence and National Research Council – Future Offensive Vehicle Prognostics and Health Management Project

NRC Activity

IAR Contact: Institute for Aerospace research

Propulsion Group Leader: Mr. Jeff Bird, Phone: (613) 993-2425, email: [email protected]

IIT Contact: Institute for Information Technology

Integrated Reasoning Research Officer: Dr. Sylvain Letourneau, Phone: (613) 990-1178, email: [email protected]

Activity Description:

Research activities will be conducted in four domains as follows:

Damage Accumulation and Monitoring

• Processes o Physics of failure (data- and model-based): pre-cursors o Bearings- static, dynamic and lubrication effects o Gas path- aero, LCF, HCF,…with relevant environment

• Monitors o Sensors- non-intrusive and imbedded o Smart sensors with real time, dynamic capability o Non-traditional Non-destructive Evaluation applications

Life Remaining Assessment

• Application of Damage Process understanding • Failure Mode and Criticality Analysis – available? • Integration of damage accumulation sensor data • Operational usage measurement and extrapolation

Decision Reasoning Tools

• Integrated reasoning and data fusion • Data mining • Enterprise information and decision management • Hybrid reasoning- case-based with model-based

Health Management

• User tools and field application: software and hardware • Capture of knowledge: cases, processes, non OEM data • Cost effectiveness data and analysis for complete PHM process • Identification of opportunities: durability, reliability

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Activity Title: US Air Force Research Laboratory (AFRL) Propulsion Directorate

Website: http://www.pr.afrl.af.mil

Activity Description:

At the “Technology & Programs” weblink on this page, there are links to the following programs that represent relevant activities for the DPHM. Excerpts are taken from each of these programs and inserted in subsequent tables for each of the relevant programs:

• High Cycle fatigue (HCF);

• Integrated High Performance Turbine Engine Technology (IHPTET); and

• Versatile Affordable Advanced Turbine Engines (VAATE)

Please note that there are other relevant programs targeted at hypersonic propulsion and other advanced vehicle domains that are considered outside of the terms of reference for this current study.

Activity Title: US Department of Defense AFRL High Cycle fatigue (HCF)

Website: http://www.pr.afrl.af.mil/divisions/prt/hcf/2002report/

Activity Description:

The website listed above provides a link to the 2002 HCF Annual report.

The following summary is taken from the AFRL Technology & Programs page:

High cycle fatigue results from vibratory stress cycles induced from various electromechanical sources. It is a widespread phenomena that, historically, has led to premature failure of major turbine engine components. This national program was established in 1994 to help eliminate high cycle fatigue as a major cause of these failures. Program participants include Air Force, Navy, NASA and an industry panel. The program's objectives include a 50% reduction of high cycle fatigue related engine maintenance costs.

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Activity Title: US Department of Defense (AFRL) Integrated High Performance Turbine Engine Technology Program (IHPTET)

Website: http://www.pr.afrl.af.mil/divisions/prt/ihptet/ihptet.html

Activity Description:

The following summary is taken from the AFRL Technology & Programs page:

The Integrated High Performance Turbine Engine Technology (IHPTET) program, started in 1988, has an aggressive technology development plan to leapfrog technical barriers and deliver twice the propulsion capability of today's systems by around the turn of the century. Unprecedented teaming of the Army, Navy, Air Force, NASA, ARPA and industry, in each of the technology areas, is underway. The main focus of these "Technology Teams in Action" is to advance military aircraft superiority through high performance, affordable, robust turbine engines.

This program has been underway for a number of years and has provided a template for US DoD R&D programs in virtually all technology domains. The IHPTET has been extended a number of times and will phase into the VAATE which is described in the following table.

Activity Title: US Department of Defense (AFRL) Versatile Affordable Advanced Turbine Engines (VAATE)

Website: http://www.afrlhorizons.com/Briefs/Dec01/PR0105.html

Activity Description:

The weblink is to a paper describing the VAATE. Excerpts from that paper are inserted below:

“The Propulsion Directorate initiated conceptual studies to help define the successor to the highly successful Integrated High Performance Turbine Engine Technology (IHPTET) program. This follow-on effort, called the Versatile Affordable Advanced Turbine Engines (VAATE) program, will extend IHPTET's predominant focus on improving engine performance to encompass total propulsion system affordability—the amount of capability acquired for a given cost. The goal of VAATE is to increase turbine engine affordability tenfold. Researchers must continue to develop capability-enhancing technologies along with a new emphasis on technologies to reduce engine development, production, and maintenance costs to achieve this aggressive goal.

The VAATE program, structured around three focus areas, emphasizes specific themes important to achieving the affordability goal. The first area, the Durability Focus Area, will proactively develop, design, and test protocols to prevent component failure, increase life, enhance reparability, and ultimately improve performance. The second area, the Versatile Core Focus Area, will develop technologies for a multi-use, 4000-hour, maintenance-friendly engine core (compressor, combustor, and turbine). The third area, the Intelligent Engine Focus Area, will develop and integrate technologies that provide durable, adaptive, damage-tolerant engine health and life management features.

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Activity Title: US Air Force Research Laboratory - Air Vehicles Directorate

Website: http://www.va.afrl.af.mil/

http://www.va.afrl.af.mil/FA/Sust/sust_tech_areas_index.html#damage_mang

Activity Description:

The Air Vehicles Directorate supports a sustainment technology area entitled Damage management for which an overview chart is located at the second weblink above. This technology area and the activities supported thereunder are of direct relevance to the Industry Canada DPHM initiative.

This technology area supports technology development for existing and advanced aircraft systems as well as Unmanned Air Vehicles.

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Activity Title: Propulsion Instrumentation Working Group (PIWG)

Website: http://www.oai.org/PIWG/

PIWG Technology Listing and Subteams: http://www.oai.org/PIWG/Technology.html

Lab Gap matrix:

Activity Description: Taken from the PIWG website

The PIWG was formed in 1995 in response to an environment of shrinking research and development resources. By agreeing to treat propulsion engine test instrumentation as “precompetitive,” PIWG is able to help focus scarce R&D resources on a matrix of test instrumentation deficiencies (termed by PIWG as “lab gaps”) and potential solution technologies.

Industry participants of PIWG include: General Electric Engines, Honeywell International; Pratt and Whitney, Rolls-Royce, Siemens Westinghouse and Williams International.

Participating Government Organizations include: Air Force Arnold Engineering Development Center (AEDC), Air Force Research Lab (AFRL), NASA Glenn Research Center, and Naval Air Warfare Center Aircraft Division (NAWCAD).

The Ohio Aerospace Institute serves as the facilitator to PIWG.

Based on survey input from PIWG’s membership, a matrix of the lab gaps (areas where development efforts were required to meet anticipated instrumentation needs) and potential technological solutions was formulated. It is at the intersections of the identified lab gaps and the potential instrumentation and sensor technology solutions for these gaps that PIWG focuses its collective energies and resources to develop state-of-the-art instrumentation and sensor technologies. The size and diversity of the lab gap list are such that the group as a whole cannot expect to make progress in an acceptable time frame. To facilitate progress PIWG has formed technical subteams in areas of interest composed of technical specialists from member organizations chosen for their expertise in their particular disciplines. These subteams meet on their own, either through teleconferencing or in person, to address technologies in their fields. The subteams report their progress and plans to PIWG at regularly scheduled meetings.

The PIWG subteams are listed below: • Microsensors; • Surface Temperature; • Strain Measurement; • NSMS (Light Probe); • Slip Ring; • Emissions; • Telemetry; • Dynamic Pressure; • Gas Temperature; and • Surface Pressure.

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Activity Title: NATO Research and Technology Organization

Website: http://www.rta.nato.int/

Activity Description:

The NATO Research and Technology Organization (RTO) consists of the following Technical Panels:

• Applied Vehicle Technology (AVT);

• Human Factors and Medicine;

• Information Systems Technology;

• Studies, Analysis and Simulation;

• Systems Concepts and Integration; and

• Sensors and Electronics Technologies.

A number of these Technical Panels have projects of interest to the DPHM initiative although the majority of the open activities are under the Applied Vehicle Technology (AVT) Technical Panel as described below. The website shown above provides links to the various Technical Panels where one can then link to the Activities of the Technical Panel, both current and completed.

Activity Title: NATO Research and Technology Organization

Website: http://www.rta.nato.int/

Activity Description: Applied Vehicle Technology (AVT) Panel

The Mission of the Applied Vehicle Technology (AVT) Panel is to improve the performance, affordability and safety of vehicle platforms, propulsion and power systems through the advancement of appropriate technologies. The panel addresses technology issues related to vehicle platforms, propulsion and power systems operating in all environments including land, sea, air and space, for both new and aging systems.

Open AVT Activities of potential interest to the DPHM initiative are listed below:

Reference Title Ends

AVT-051 Enhancing Air Vehicle Inspection Reliability 2004

AVT-105 MEMS Aerospace Applications 2004

AVT-100 Vehicle Propulsion Integration 2004

AVT-086 Application of Adaptive Structures in Active Aeroelastic Control Not Published

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Activity Title: Canadian Nano Business Alliance

Website: http://www.nanobusiness.ca/

Activity Description:

The following companies or government agencies are listed at the Canadian Nano Business Alliance website under the under A2. Aerospace & Defence Nanomaterials & Devices:

• Aiolos Engineering, Toronto, ON • CANEUS, Montreal, QC • Canadian Space Agency, St-Hubert, QC • CLS3, Montreal, QC • COM DEV International, Cambridge, ON • CRIAQ, Montreal, QC • Defence Research & Development Canada, Val Cartier, QC • Pratt & Whitney Canada, Boucherville, QC • Scintrex Trace Corp, Ottawa, ON

No specific technology initiatives are identified on the Association website.

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Activity Title: CRIAQ – Microsystems for In-Situ Health Monitoring of Aircraft

Website: http://www.criaq.org/English/

http://www.criaq.org/English/6_1.html

Activity Description: MEMS (Micro-Electro Mechanical Systems)

Project 6.1 Microsystems for In-Situ Health Monitoring of Aircraft

The following organizations are involved in this project:

• Université de Sherbrooke, (Institutional Leader); • Bombardier Aéronautique (Industrial Leader); • National Research Council Canada; • École Polytechnique; • École de technologie supérieure; • Université McGill; • Université de Sherbrooke

The research objectives of this project are as follows:

• to develop methodologies for incorporating advanced sensors and actuators for monitoring the health of aircraft structures;

• to develop analytical and numerical modelling tools, as well as data processing methodologies for the design and assessment of the structural and electromechanical integrity of the instrumented structure;

• to conduct experimental investigations for proof-of-concept and validation of analytical and computational methodologies. This project aims at reducing the high costs associated with periodic prescribed inspections of aircraft, usually requiring the dismantling of some components of the structure, by the development of an in situ structural health monitoring (SHM) system. The system will provide, either passively or actively, real-time in situ structure load transfer profiles, identifying the efficiency and health of the structure, to an on-board data acquisition system. Load profiles will be analyzed and evaluated against preset failure threshold marks for the issuance of an alarm signal.

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Activity Title: CRIAQ – MEMS Based Gas Turbines Control

Website: http://www.criaq.org/English/

http://www.criaq.org/English/6_2.html

Activity Description: MEMS (Micro-Electro Mechanical Systems)

Project 6.2 MEMS Based Gas Turbines Control

The following organizations are involved in this project:

• Université Concordia (Institutional Leader); • Pratt & Whitney Canada (Industrial Leader); • Canadian Microelectronics Corporation; • Case Western University; • Concordia University; • École Polytechnique; • École de technologie supérieure; • McGill University; • Simon Fraser University; • Université de Sherbrooke

The research will be focusing on the development of microsensors that are not available in the market to be used in the control and monitoring of gas turbines. The research will be directed toward sensors that can measure in a high temperature environment and can monitor the composition of the exhaust gases that will provide clues on the functioning of the engine. It is expected that the implementation of the above systems will enable a significant enhancement in the gas turbine performance and reliability.

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Annex B - Aeropropulsion DPHM Requirements and Technology Descriptors

B1 Systems Requirements

B1.1 Systems Requirements Overview Although aircraft have become much more complex in the last fifty years, much of the maintenance philosophy and many of the tools for ensuring serviceability have remained essentially unchanged. And, while new aircraft with advanced health management systems designed-in will enter the market in the coming years there will be a continuing need to support and enhance legacy DPHM systems with advanced health management functionality. Four generations or classes of DPHM systems are identified below, beginning with current systems functionality. With each step in the evolution of DPHM systems one will see increased functionality, greater discrimination in terms of fault diagnosis or prognosis, increased on-board and autonomous analysis, and ever greater integration of the DPHM systems with the enterprise supply chain.

• Current Systems: Largely characterized by preventive maintenance where parts are changed based on calendar time or flying/operating hours, or alternatively when they break;

• Reactive Health Monitoring: This implies run-to-fail for components which are typically not flight critical, a basic on-condition monitoring approach depending on built-in-test, and otherwise largely ground inspection and test processes;

• Proactive Health Monitoring: This approach forecasts future failures and institutes corrective action in a manner which is cost-effective least disruptive to operations; and

• Intelligent Engine/Active Management: This approach entails on-board assessment of damage mode accumulation and minimizes damage through the use of redundant systems or changes in system loads.

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Figure B-1 – DPHM Systems Evolution

B1.2 System Functionality Map Table 1 below provides an initial view of the DPHM systems functional requirements decomposition. In this table an attempt is made to identify sub-functions within each of the diagnostics, prognostics and health management top level functions. Many of the DPHM sensor and analysis technologies and concepts are common to all three top level functional groups. No attempt has been made in this table to identify whether the functions are carried out on-board the aircraft or post-flight nor whether or not they are autonomous.

Table B- 1 – DPHM Top Level System Functionality Map

Diagnostics Prognostics Health Management

Data Collection and Communication – Knowledge Management

Failure Mode, Effects and Criticality Analysis

Fault Assessment Fault Detection

Component Life Tracking Fault Reporting

Life Remaining Analysis Fault Accommodation

Performance Trending

Fault Isolation

Fault Prediction

Supply Chain Integration

Current/ Preventative

Reactive Health Monitoring

Proactive Health Management

Intelligent Engine/ Active Management

2004 2006 2008 2010 2012 2014 2016 2018 2020

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B1.3 Data Collection and Communication In the systems functionality map that is contained in Table 1 above an attempt has been made to decompose, diagnostic, prognostic and health management functions down one level. Many of these second tier functional requirements are applicable to more than one top level functionality however. Also, it is evident that the data collected for diagnostics will typically be equally applicable to prognostics functionality and that knowledge management will become a significant and ubiquitous functional requirement. The intent of this section of the document is to develop a common lexicon for DPHM functional requirements. Functional requirements are therefore described in non-exhaustive detail in subsequent paragraphs.

B1.4 Diagnostics Earlier in the document, diagnostics was defined as the process of determining the state of a component to perform its function(s) based on observed parameters. In general, the term diagnostics is applied to that part of the maintenance process that occurs after an engine or system dysfunction has been manifested in a manner that renders the engine and aircraft as likely being unfit for its full mix of missions and roles. Diagnostics is often considered a two step process, the first being the identification that a fault has occurred and then localizing the cause of the fault to a specific component, ideally at the lowest assembly level to reduce costs.

B1.5 Fault Detection Faults may be system dysfunction that is abrupt and continuous or virtually unobservable yet having the potential to adversely affect the engines capability to perform future missions. A fuel control unit (FCU) that ceases to properly manage the full engine operating spectrum is a readily observable case of the former whereas a partial system failure that results in short duration speed spikes that may not be observable to the flight crew is an example of the latter. Fault detection is effected by on-board instrumentation and analysis systems or by flight crew observation of system anomalies. As for prognostics functionality, the definition of system faults must be categorized in accordance with a thorough Failure Mode, Effects and Criticality Analysis (FMECA). The fault detection requirement is to identify faults of a specified magnitude in a complex system having many interdependent sub-systems.

B1.6 Fault Isolation Faults in a complex system are not always obvious and the root cause of a problem may be hidden by the symptoms that arise as other dependent sub-systems respond to the core fault. An example of this complication can be taken from an aircraft with on-board diagnostics systems that may raise several dozen fault codes as a result of a problem and the subsequent error messages that are produced as interdependent systems react to incorrect inputs. While it is hoped that aircraft systems in the future will be entirely self diagnostic, there must be some accommodation made for the elusive or unforeseen faults that will continue to occur and which will always require human ingenuity to address.

Fault isolation utilizes built-in-test, on-board and ground based test equipment as well as numerous maintenance aids for collecting and analyzing data. Many of the existing systems however provide so much spurious data as to often be of little utility in either the fault detection or isolation role. A complication is experienced when the DPHM sensors

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fail or drift in calibration and this factor imposes additional requirements as the DPHM system must also be capable of recognizing when it has failed.

Nevertheless, the DPHM systems objective is for increasing autonomy for on-board diagnostic aids with improved fidelity in the fault isolation process such that the lowest and least expensive replaceable faulted unit can be removed or repaired. To achieve this end as well as those mentioned earlier, sensors used for fault detection must be smaller, less costly and more reliable. This has proven to be an area of great interest for Micro-Electro Mechanical Systems (MEMS) technology application.

B1.7 Prognostics As defined earlier prognostics is predictive diagnostics that includes determining the remaining life or time span of proper operation of a component. This implies understanding the damage modes which will determine the acceptable service life of a component, tracking the rate of damage accumulation and being able to intelligently forecast, based on ever changing mission demands, the acceptable service life of a component. Prognostics functionalities are discussed under five headings or sub-functions:

• Failure Mode, Effects and Criticality Analysis (FMECA);

• Component Life Tracking;

• Life Remaining Analysis;

• Performance Trending; and

• Fault Prediction.

B1.7.1 Failure Mode, Effects and Criticality Analysis (FMECA) A Failure Mode, Effects and Criticality Analysis (FMECA) is a process for identifying potential failure modes and classifying them according to both the severity of their effects on the system as well as the probability of their occurrence. FMECA’s are often two part processes wherein failure modes and their effects Failure Mode and Effects Analysis (FMEA) are identified first and both the severity and the probability of occurrence for the failure mode (CA - Criticality Analysis) are defined in the second step of the process.

The FMECA process is typically undertaken in the following manner:

• Construct a model or block diagram of the system being analysed;

• Identify failure modes for all major sub-systems;

• Attempt to define primary and secondary effects of the failure mode;

• Classify the severity of the malfunction in terms of mission parameters;

• Based on systems knowledge including fault detection systems and probabilities of detection for all detection systems and techniques, identify the probability of occurrence for the fault; and

• Rank failure modes in terms of severity and criticality.

The FMECA approach is well documented with numerous private sector concerns offering comprehensive and effective competency.

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B1.7.2 Component Life Tracking Component life tracking is a complex subject that poses significant challenges to both sensor and analysis technologies. In the past, component life was determined based on design data and an anticipated mix and severity of operational missions. This resulted in a worst case life scenario being applied with components being removed from service with only a fraction of their actual safe life having been consumed. While this was advantageous for the suppliers of the components it represented a tremendous cost burden for owners and operators of aircraft.

As sensor technology is increasingly miniaturized and computation power as well as on-board memory storage performance increases, it became possible to track individual component damage accumulation on-board in real time. Low cycle fatigue counts for rotating component, pressure-burst analyses for combustors and time-at-temperature for creep analyses can be monitored individually and used to complement human observations of the state of components and their probability of satisfactorily enduring the rigours of the next mission. The analysis of oil-wetted component debris was likely the first of the prognostic technologies to offer significant, reliable and effective prognostics information on bearing, spline, and gear and hence engine operation life remaining.

Component life tracking and its enabling technologies has been and will in the future continue to be a key focus area for prognostics utility. Relevant technologies continue to evolve in this domain and this is nowhere more clearly demonstrated than in the F100 Engine Seeded Fault trials being supported by the US DoD for both the JSF and VAATE programs. Advanced sensor technologies as well as analysis techniques are highlighted in Figure B-2 below for illustrative purposes.

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Figure B-2 – F100 Seeded Fault Engine Test DPHM Technologies Extracted from a UD DoD JSF PHM Presentation.

Legend for Figure 4:

AFD - Acoustic FOD (Foreign Object Damage) Detector BVM8X - Blade Vibration Meter EBM - Electrostatic Bearing Monitor ECS - Eddy Current Blade Sensor EDMS - Engine Distress Monitoring System EODM - Electrostatic Oil Debris Monitor IDMS - Ingested Debris Monitoring System OCM - Oil Condition Monitor PZT - Piezoceramic Patch Crack Detection RLI - Robust Laser Inferometer SWAN - Stress Wave Analysis Vibes - Vibration monitoring

B1.7.3 Life Remaining Analysis The analysis of the remaining service life of a component is extremely challenging in light of the technological challenges as well as the need for proprietary design information that is often, but not always, necessary for this DPHM function. The

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scientific challenges associated with life remaining analyses are discussed in more detail later in this document.

The functional requirement can be summarized as being the accurate prediction of the remaining useful life of a component based on the life limiting damage mode, damage accumulated on a real-time basis and the operational demands that will be imposed on the system between the point in time where the analysis is being made and that time when dysfunction will occur.

B1.7.4 Performance Trending Performance trending involves monitoring of typically a family of parameters which provide a normalized appreciation of the state of a components performance with respect to an acceptable level of performance. Perhaps the most obvious performance parameter is that of thrust or horsepower produced. In this case an engine when first produced or overhauled will have a performance output that exceeds the minimum required for its contribution to safe flight. As wear occurs the engines performance may degrade to the point where its performance is unacceptable, or potentially unacceptable under certain flight scenarios, hot and high, one engine out etc. Other operational requirements may however recommend a maintenance action prior to a component becoming unsafe for flight under all conditions. To use the previous example, an engine’s output may continue to be operationally satisfactory but at the expense of excessive fuel consumption, and this may require that appropriate action be taken when the benefits of that action exceed the costs.

Performance trending may occur in many ways from human observation of instruments to dedicated on-board systems recording a large number of parameters. The trending may occur against absolute values, model generated values or even against other similar systems on the aircraft. Regardless of the manner of, or parameter being trended, this is a key DPHM functionality and one that is particularly amenable to retrofit on existing systems. It is also an area where science and overall enterprise performance parameters overlap and where proprietary design knowledge may be of lesser importance than actual operating knowledge of a system.

B1.7.5 Fault Prediction Fault prediction is the forecasting of the point in time where the performance of a component is unacceptable. That unacceptability may be expressed in many ways as described in the foregoing paragraphs. Once again, on-board fault predictive capabilities are increasingly sought but tempered with knowledge management considerations. Ensuring that the right people in the operational and logistics chain are aware of faults predicted will be a key to enterprise success.

B1.8 Health Management Health Management was previously defined as being the capability to make appropriate decisions about maintenance actions based on diagnostics/prognostics information, available resources, and operational demand. The challenge to health management is to make efficient and effective corporate level decisions on engine assets based on a very large amount of available diagnostic and prognostic information that is being generated. Ideally, the health management functionality will make the maintenance and logistics decisions automatically or at least present the planner with the benefits and drawbacks of the preferred set of options.

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For the purposes of this study, health management functionality has been divided into the following four sub-functions:

• Fault assessment;

• Fault reporting;

• Supply chain integration; and

• Fault accommodation.

B1.8.1 Fault Assessment Fault assessment refers to the appraisal of the significance of the failure and its effect on existing and future serviceability of the aircraft in question. If a particular system on an aircraft is not functioning, does that impact on the airworthiness of the aircraft or on its ability to fulfill its planned missions? In the case of a multi-function military aircraft with an un-serviceability in a ground support mission system, can the airplane be used for Combat Air Patrol and are other assets available for the ground support role? The questions that are addressed by the fault assessment function can be summarized as:

• Is the aircraft safe for flight now, and if so, how much longer will its airworthiness be within acceptable limits? and

• If the aircraft is not considered safe for flight with an existing or incipient malfunction, what options are available to mitigate damages as well as protect the persons on-board as well as physical assets?

B1.8.2 Fault Reporting Fault reporting has a number of dimensions characterized by the reporting required and appropriate for flight crew and/or for other organizations within the enterprise. Current DPHM systems often provide too much, or not the right type, of information to the aircrew. The primary purpose of this functionality is to advise the pilot or if appropriate, other flight crew of an impending dysfunction or emergency and offer alternatives for continued safe flight. This is a key requirement but is also one that is fraught with airworthiness regulatory issues.

B1.8.3 Supply Chain Integration The objective of this functionality is to advise the supply chain of the requirement for a component as soon as possible after an aircraft DPHM system has identified an existing or imminent fault. This functionality is the least implemented of all the DPHM functionality discussed to date and can either be man-in-the-loop, or ideally completely automated. Parts availability and location, as well as shipping instructions will potentially be generated as part of this functionality. Workbay and personnel requirements and availability may also be communicated to the appropriate organizational element as part of this functionality.

B1.8.4 Fault Accommodation Fault accommodation is a key focus area for the US DoD VAATE program which targets technologies for the “intelligent engine”. Fault accommodation is intended within this document to address a number of requirements which are briefly discussed below:

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• To identify faulted components, whether they be engine or DPHM sensors, and employ redundant systems or software to ensure that engine functionality is maintained and collateral damage is reduced or precluded;

• To extend the operating life of the engine by sensing the onset of entry in an accelerated damage accumulation mode and alter the engine operation, without adverse mission effect, to mitigate or eliminate the damage occurring;

• To accommodate gradual system degradation by intelligent use of redundant systems or operating procedures; and

• To minimize the costs of operation by altering engine operation, without significant adverse mission effects, to achieve increased component durability or by matching component life usage amongst the various engine modules or components.

Fault accommodation defined in this manner represents perhaps the ultimate challenge and systems functionality of the DPHM system.

B2 Technologies

B2.1 Advanced DPHM Technologies Overview Reference [5] provides the list of representative advanced Condition Based Maintenance (CBM) sensor technologies and applications that is presented in Table B-2. Many of these technologies have been in use for some time but require increased reliability, miniaturization and lowered costs to be utilized in on-board DPHM systems.

Sensor Technology Application

Ultrasound Wall thickness, Hydraulic/Pneumatic Leaks

Infra-red Motors, pumps, bearings, Electronics, Heat Stress

Ferrography Oil, Analysis, Detection of Wear Metals

Laser Structures, joint alignment/separations, particle detection

Eddy Current Anomaly detection, turbine blade cracking

Gas chromatography Exhaust analysis

Acoustic Plastic deformation of materials, Seal leaks

Spectrum Analysis Electronic Emissions Table B-2 – Advanced JSF Condition Based Maintenance Technologies The list of sensor technologies contained in Table B-2 is not exhaustive nor is it implied that sensor technologies are the only ones of interest to this DPHM Technology Insight Document.

A list of the primary DPHM technologies of interest is provided in below. Subsequent paragraphs briefly describe those technologies. This document is not intended to be an engineering textbook in the description of these technologies but rather to briefly introduce the concepts, goals and objectives of the technologies.

• Metallurgical Life Limit Monitoring;

• Crack Detection and Monitoring;

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• Oil Condition Monitoring;

• Gas Path Monitoring including debris, flame condition etc;

• Vibration Analysis;

• Physical Alignment;

• Aero-thermodynamic Performance Assessment;

• Decision Aids/Reasoning Engines;

o Rules Based Reasoning; o Case Based Reasoning; o Model Based Reasoning; o Neural Networks; and

• Health Management/Supply Chain Integration.

B2.2 Metallurgical Life Limit Monitoring The following metallurgical life limiting damage modes are discussed in the paragraphs following:

• Low Cycle fatigue (LCF);

• High Cycle Fatigue (HCF);

• Thermal fatigue;

• Stress/corrosion monitoring; and

• Creep;

Low Cycle fatigue (LCF) Low cycle fatigue (LCF) results in failures which occur at typically less than 100,000 cycles of load reversals from min to max and back to minimum stress levels, or relatively high average stress levels. In a rotating component, this is often strongly correlated to the start-stop cycle where the rotating components of an engine go from zero stress at start, to maximum rotational stresses at peak or operating RPM, and then back to zero when the engine is stopped. LCF failures typically originate from a flaw in the material such as a void or impurity or from an area of high stress concentration such as a machining flaw or service induced cracks where high stress concentrations are experienced. LCF life analysis is complicated somewhat for transient engines where high cycle fatigue type stresses are overlaid on the LCF stresses and depending on the severity and load sequencing and frequency can lessen the life of a component.

LCF is normally monitored by counters that keep track of the start-stop cycles as well as transients in RPM that exceed certain excursion limits.

High Cycle Fatigue (HCF) A failure may be considered High Cycle Fatigue (HCF) if dysfunction occurs after a large number of typically low average stress fluctuations, typically more than 100,000 cycles. The number of load cycles identified for both HCF and LCF should be taken as representative rather than definitive. HCF loads are typically the result of fluctuations

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caused by aerodynamic instabilities, resonance or other vibratory loads. As the excitation is most pronounced in components such as fan or compressor components the failure may progress rapidly with catastrophic consequences. HCF is considered to be a significant problem by the US DoD who feel HCF may be responsible for as much as 50% of all engine failures. In 1994 the US Air Force Air Force Research Lab (USAF AFRL) initiated a joint service HCF program for which the latest annual report is identified at Reference [7.]. That report contains additional information on relevant HCF monitoring technologies.

Thermal fatigue

The NASA definition for thermal fatigue is: “In metals, fracture resulting from the presence of temperature gradients which vary with time in such a manner as to produce cyclic stresses in a structure”. Thermal fatigue is result of temperature differentials within a component which may result in stresses that are much greater than the centrifugal stresses to which a component is exposed. The cyclic nature of the thermal stress is analogous to the LCF stress environment described earlier and may be best exemplified by examining a cooled turbine blade. In the first instance the cold turbine blade will be exposed to a high temperature gas stream at start-up and subsequently be required to cool down from high temperature at engine shut down. The stress fields tend to be very complex which makes failure modeling difficult. The cracks which occur as a result of thermal fatigue may often also be difficult to monitor although a number of real-time techniques have been developed, some of which are identified in Figure 4.

Creep

Creep is failure that is due to prolonged periods of component stress at elevated temperature operating conditions. Creep can result in turbine blade failure modes such as blade untwist or more usually blade lengthening. As for many of the metallurgical life limiting damage modes the typical monitoring approach is to develop accurate and often complex models which are fed with data collected from operating engines. This allows on-board monitoring or assessment of creep life usage however this is often not an environment where sudden failure occurs.

B2.3 Crack Detection and Monitoring Crack detection and monitoring techniques run the full gamut from off-line visual techniques to a variety of non-destructive evaluation methods. These methods which typically require engine and component disassembly have been well described and implemented for aviation systems and considerable Canadian technology competencies exist.

In recent years, there has been a number of real-time crack detection technologies developed which are at various stages of implementation maturity for AAMS applications. Some of those technologies include:

• Conventional off-line non-destructive evaluation;

• Acoustic emission;

• Stress wave analysis techniques; and

• Capacitive discharge sensors.

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B2.4 Oil Debris Monitoring The monitoring of debris generated within an AAMS component and contained in the lubricating fluid or fuel has been long studied and a number of methods have been implemented to monitor damage accumulation as well as forecast component failure. A survey of this field will result in the observation that there is a strong desire to achieve on-line rather than off-line oil analysis methodologies. Implementation of a PHM strategy suggests that on-line is a future requirement and breaks down into:

• analysis of oil chemistry

• analysis of oil debris

On-line analysis of oil chemistry is in its infancy. It is by no means a certainty that bench top methods such as spectroscopy will scale to a robust on-line form. Much work lies ahead.

On-line analysis of oil debris exists in a very robust and mature fashion for metallic particulate but methods of accurately and reliably detecting and quantifying non-metallic debris do not exist at present. As with all detection methods, it is useful to continue to research methods of improving detection thresholds.

The progress of PHM will be greatly slowed without continued emphasis on corroborating technologies by which the onboard assessments are confirmed by fast and robust ground based techniques. Oil monitoring will thus focus on such technologies as filter analysis and both chemical and metallurgical analysis of material removed from the filter. This will make use of both spectroscopic and EDXRF technologies as well as other more specific measurements such as viscosity and acidity. The key here is speed and ease of use which suggests that these technologies will be repackaged and moved from the laboratory to the flight line which, in turn, means addition of intelligent agents which will eliminate the need for speciality skills.

B2.5 Gas Path Debris Monitoring Inlet FOD Detection

{Taken from http://www.shl.co.uk/Technologies/Electrostatics/Pages/gas_path_debris_monitoring.htm

Stewart Hughes Ltd Now part of Smith Electronic Systems}

Inlet FOD detection was originally developed to protect large engine from stall/flameout due to bird ingestion and this technology has been developed and refined by Stewart Hughes Ltd for a number of years. The overall concept of Inlet Debris Monitoring system (IDMS) is that it detects the electrostatic charge carried by debris ingested into the engine.

In the JSF installation, the Stewart Hughes IDMS utilizes two ring sensors installed in the intake of the engine together with the EDMS sensor in the exhaust duct of the engine. Data is continuously acquired and processed from all three sensors. When a piece of debris is detected by the IDMS sensors, certain characteristics are combined to produce an assessment of its damage potential (i.e. non-damaging or damaging). The data is correlated with EDMS results to determine the resultant effect of the ingested object on the engine.

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Exhaust Gas Debris Monitoring

{Taken from http://www.shl.co.uk/Technologies/Electrostatics/Pages/gas_path_debris_monitoring.htm

Stewart Hughes Ltd Now part of Smith Electronic Systems}

The Engine Distress Monitoring System (EDMS) detects the electrostatic charge associated with debris present in the exhaust gas of a jet engine. The EDMS monitors gas path component deterioration in real time and provides early warning of incipient fault conditions. The severity of the fault may be tracked, thereby allowing greater freedom in maintenance planning. Fault discrimination to engine module level is possible and so EDMS may be used to promote timely application of fault specific diagnostics. EDMS also monitors faults, for example combustor degradation, which are not readily detected by other techniques.

A sensor is installed in the exhaust duct of the engine and data continuously acquired and processed. The data is generally normalized with the engine fuel flow or other suitable parameter and processing includes correlation with each of the engine spool speeds. Diagnostics have been developed to detect and identify the nature of the fault, for example a blade rub, combustor fault etc.

IR Thermography

IR thermography utilizes the IR signature of a component to identify such characteristics as seal leaks, turbine exit thermal profiles and evening bearing or gear distress that is giving rise to increased thermal output. IR thermography can be used in real-time or as a trending tool to analyse thermal signature changes over time. The reduction in cost of thermal imagers and increasing robustness of the sensors may enable increased use of this technology in airborne systems.

B2.6 Vibration Analysis Vibration analysis (VA) involves the measurement of localized component velocity, acceleration or displacement. Limits at various engine locations are specified for each or at least one of these parameters for engine pass of test. If the AAMS system were a simple system with few moving parts then the VA challenge would be inconsequential, however VA has received a significant investment in R&D resources as advanced technologies have been applied in an attempt to understand what specific component is producing the vibration and the source of the vibratory energy.

Vibration analysis has also spawned innumerable vibration test programs and continues with the F100 Seeded engine fault trial earlier depicted. There is a large volume of vibration analysis reference material available for engine, gearbox, individual gear, and shaft analyses and condition monitoring and no attempt will be made in this document to present this large topic area.

One new topic, deriving from the F100 Seeded Fault Engine trial relates to the analysis of airfoil/blade vibrations. In this instance blade vibration is used to detect the onset of aerodynamic instability rather than an abnormal wear or weight imbalance problem.

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B2.7 Physical Alignment Physical alignment is a major issue with rotary wing aircraft although has very limited application for fixed wing aircraft other than in the assembly of engines after overhaul or in aircraft symmetry and alignment verification.

Shaft Alignment for rotary wing a/c remains a major issue due to the dynamic nature of the a/c structure. It is believed that a more direct on-line methodology for continuous monitoring of shaft alignment is worth pursuing.

B2.7.1 Clearances Clearances are an issue with high performance engines wherein there is an attempt to design to minimize air leakage losses due to variations in the growth of rotating and non-rotating parts as a consequence of operation at different temperatures. Attempts to achieve minimum leakage have focused on abradable seals and/or active seal control. Some on-line clearance technologies are being pursued in advanced engine programs including the JSF propulsion system.

B2.7.2 Aero-thermodynamic Performance Assessment The use of aero-thermodynamic data as a means of assessing the condition of an engine has proven effective for a wide variety of engine problems that are manifested by changes in overall performance. Many of the observed changes in rotor speeds, temperatures and pressures can be linked to a root cause which reflects physical changes to the gas path components.

Engine degradation modes for which successful diagnostic parameters have been developed include:

• tip clearance changes

• variable geometry wear

• variable geometry control malfunction

• fuel system malfunctions

• turbine nozzle bowing

• turbine blade damage

These techniques tend to require multiple gas path measurements and are frequently specific to a given engine.

The concept of integrating these condition assessment techniques with adaptive control techniques is now being explored.

Much of the foundational knowledge base for the development of performance based diagnostics has been established, i.e. the basic cause/effect relationships are either known or can be determined with appropriate tools. However, much research work is required in order to select appropriate indicators from the suite of sensors that are either fitted or possibly can be fitted. Thus, a full compendium of a fault library remains elusive.

Alternatives to the fault library approach involve a combination of model based reasoning and are of several self-learning expert systems (e.g. Neural net, Baysian Nets, etc.) This is an area of basic research that is still some ways off but bears fruit if

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tackled properly. Its principal appeal is the possibility of adaptation to new emerging problems on a specific engine type without a wholesale rework of the fault logic. The principal likely limitation is the number of dimensions of the learning domain that make practical implementation difficult or doubtful.

B2.8 Decision Aids/Reasoning Engines Often there is confusion regarding the types or reasoning that are applied to decision aids and this section attempts to identify four basic approaches to artificial intelligence/expert systems as described below. These descriptions are intended only to establish a common terminology baseline and the implementation of these approaches will be more fully developed by the industrial participants in the DPHM TID.

B2.8.1 Rules Based Reasoning Rules base reasoning is a basic Artificial intelligence approach which uses "if-then-else" rule statements. These “rules” are simply patterns and the reasoning engine will search for patterns in the rules that match patterns in the data. The "if" means "when the condition is true," the "then" means "take action A" and the "else" means "when the condition is not true take action B. Rules can be forward-chaining, or data-driven reasoning, because they start with data or facts and look for rules which apply to the facts until a goal is reached. Or rules can be backward-chaining, or goal-driven reasoning, because they start with a goal and look for rules which apply to that goal until a conclusion is reached.

B2.8.2 Case Based Reasoning Case-Based Reasoning (CBR)refers to both a cognitive and a computational model of reasoning by analogy to past cases. A basic premise in CBR is that many problems that decision makers encounter are not unique, but rather they are variations of a problem type. It is often more efficient to solve a problem by starting with the solution to a previous similar problem than it is to generate the entire solution again from first principles. In fact, experts have been observed to reason by analogy to prior cases.

In solving a current problem, a case-based reasoner (whether it is a human or a computational model) recalls a similar past case and its solution. The reasoner then adapts the successful solution of the recalled case to adjust for any differences between the current case and the recalled case. Finally, the CBR stores the solution to the current case along with feedback about the outcome so that it can be used in solving future problems.

Typically, a CBR system consists of a data base of past cases and their solutions, a set of indices for retrieving previous cases and storing new cases, a set of rules for measuring similarity, and rules for adapting recalled case solutions. A CBR system first 'gains an understanding' of the problem. This is accomplished by collecting case attribute values that identify the problem type and that distinguish one problem type from another. The case attributes that identify the problem type are used as indices for case storage and retrieval. Indices and rules for measuring similarity focus attention on the important features of a problem, i.e., features that can be used to explain why case solutions differ.

Once the CBR "understands" the problem, it is reminded of previous similar cases. Solutions to recalled cases provide possible solutions to the new case. In interesting problem domains it is unlikely that an exact match will occur, therefore, the CBR must

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adapt its solution. Adaptation rules capture domain theory about the impact of attribute values on the solution. Learning takes place when new cases are solved and stored in the case base together with the outcome of the solution. Learning also occurs when failed solutions are attributed to specific case features and those features are then added as indices.

B2.8.3 Model Based Reasoning A Model Based Reasoning (MBR) diagnostic approach begins with a model of the system under consideration. The model must be of sufficient fidelity as to enable a full range of operational characteristics to be accurately predicted by the model under varying conditions. The more complex the system being modeled the greater are the challenges to the reasoning engine. The model based approach compares how the system is actually performing to the manner in which the model expects the system to perform given its actual operating conditions. If there is a difference between the actual and the expected values, a discrepancy exists which then must be analysed in order to determine the reason for the discrepancy.

Model based reasoning typically begins with the designer of the system whose design knowledge of the primary and dependent systems specifies all required systems inputs and responses based. This design knowledge is often of a proprietary nature which poses problems to a user/operator of a system whom does not have full access to the required data. There are a number of model based approached to diagnostics and prognostics which are very powerful applications and in fact the JSF PHM is considered to be essentially model based. A draw-back of model based reasoning is that it is typically based on static knowledge and is often difficult or expensive to grow with actual experiential data.

B2.8.4 Neural Networks An Artificial Neural Network (ANN) is typically a massive number of relatively simple co-processors operating on a system of programs and using data in a manner that attempts to simulate the operation of the human brain. Neural networks are normally tailored for the environment in which they will reason and are initially trained with data and rules about data relationships. The ANN then learns how to respond to external stimuli.

Neural networks often use principles of fuzzy logic to make determinations where the ANN is faced with a new situation. Neural networks are sometimes described in terms of knowledge layers, with, in general, more complex networks having deeper layers. In feedforward systems, learned relationships about data can "feed forward" to higher layers of knowledge.

Neural networks can learn pattern recognition and in their ultimate form will be able to fully grasp and assimilate new situations. Thus, they will not be constrained to the model based design data but will learn and function in comprehensive machine case base reasoning environment.

B2.9 Knowledge Discovery and Data Mining With the increased use of automated data capture and generation systems, exemplified in the modern DPHM system there has been an exponential growth in the data that is collected. Combining that data with human experiential data where available is often a significant challenge as we attempt to integrate both machine and human observations in the aerospace maintenance, repair and overhaul environments. There are an

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increasing number of tools that can intelligently and automatically assist us transforming these large amounts of data into useful knowledge. For the purposes of this Technology Insight Document Knowledge Discovery and Data Mining (KDD) includes all machine learning, statistical and soft computing techniques to develop diagnostic and predictive models from data.

B2.10 Data Fusion Data fusion includes techniques and software to integrate the heterogeneous data produced throughout the operation of modern and future aircraft. The end result is a global infrastructure that stores all relevant information in a coherent manner and facilitates access to this information. In turn, this infrastructure enables the application of many other advanced technologies. In fact data fusion is applied to virtually all the data generated in the modern DPHM system in order to condense the large quantities of disparate information into a usable piece of data.

Unfortunately, in the past data systems were often developed in isolated “silos” which has resulted in there being a difficulty in the re-use of available data. Increasingly however, there is an integrated systems approach being applied and this is well manifest in the Joint Strike Fighter program where data fusion requirements have been defined from the program start point.

B2.11 Health Management/Supply Chain Integration

B2.11.1 Integrated Maintenance Decision Environment The availability of large quantities of systems functional performance, prognostics and logistics data must be interfaced with a human decision maker in a manner that enables the selection of the most appropriate maintenance action based on operational requirements. While it is anticipated that many of the decisions will be made automatically using a rules based system, often it will be a human who will have to make a final decision on the maintenance action that must be taken. The integrated decision environment must at some point present a reasonable set of alternatives to the human decision maker in a manner that facilitates the decision process and links back into the machine portion of the DPHM including logistics systems.

B2.11.2 Competency Assessment and Just-In-Time Training Increasingly there is a desire to develop and deliver an integrated training environment that utilizes existing data to the greatest extent possible within the overall aerospace support environment. This support environment will include DPHM and Logistics components as well as design data, electronic manuals and training functionality. This approach reduces the costs of initial development of unique learning systems as well as the incremental change costs that result from aircraft or system configuration changes.

A logical entry point for this integrated learning concept is the DPHM systems where technicians can be provided with a full range of just in time tools, including refresher or recurrent training snippets as and when required. These training systems are evolving to the point where initial technician training, workplace tasks, and career long recurrent training can be achieved within a single environment. The learning management components of these systems track formal, as well as individual training progress. They can therefore be a convenient mechanism to uplift qualification/accreditation information

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into human resource databases, or conversely download that same information to generate work cards and assign tasks to appropriately qualified technicians.

In the Canadian Forces, this concept will be introduced as a part of the Canadian Aerospace Synthetic Environment (CASE) which envisages a distributed, but linked repository of modeling, simulation, and training assets that can be accessed by instructors, pilots or technicians when needed and as system privileges allow. This central repository of training aids augments other on-line applications that include DPHM systems and their Interactive Electronic Technical Manuals (IETM).

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Annex C – DPHM Standing Working Group Steering Committee Terms of Reference

Terms of Reference for: Aircraft Integrated Diagnostics, Prognostics and Health Management System

Standing Working Group Steering Committee

Introduction The Aerospace Industries Association of Canada (AIAC) and Industry Canada have initiated and supported the establishment of a standing Working Group for aircraft integrated Diagnostics, Prognostics and Health Management System (DPHM). Technology research and demonstration activities sponsored or promoted by the standing DPHM Working Group will encompass projects that are of strategic value to the Canadian aerospace sector.

In consideration of the multi-lateral public and private sector communities of interest, it has been deemed prudent to form a project steering committee in order to meet the expectations of all communities of interest in an efficient and effective manner.

Role The role of the DPHM Steering Committee is to provide strategic, executive direction for the Aircraft DPHM Standing Working Group. The Steering Committee keeps the DPHM Working Group membership and the AIAC Technology Council Chair informed on all aspects of the Aircraft DPHM technology implementation program and solicits input where appropriate. The Steering Committee also provides expert opinion and direction on the conduct of any technology insertion projects, and reviews and approves all documentation.

Scope

The responsibilities of the Aircraft DPHM Steering Committee include:

• Review, revise and approve the DPHM Working Group Vision and Mission statements;

• Develop mechanisms for the initiation of strategic DPHM demonstration projects and activities;

• Review, revise and approve the project management plan, monitor the performance of all relevant activities, and provide direction as appropriate to demonstration project team members;

• Provide expert specific technology or market input and direction to project teams in the performance of project activities;

• Establish format requirements and review and approve the contents of all project documentation; and

• Keep the DPHM Working Group membership and the AIAC Technology Council Chair informed of project activities and solicit advice as required.

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Membership

Position Name

Chairperson Hany Moustapha

Members:

Bell Helicopters Mr. Bob Fews

Bombardier Mr. Carlos Trindade

Pratt and Whitney Canada Mr. Eric Hosking

Honeywell Mr. Chun Ho Lam

Standard Aero Limited Mr. Kerry Boucher

GasTOPS Limited Mr. Dave Muir

CaseBank Technologies Inc Mr. Phil D’Eon

Mxi Technologies Inc Mr. Jeff Cass

Industry Canada Mr. Jim Castellano

DND Mr. Ken McRae

NRC/IAR Mr. Jeff Bird

NRC/IIT Dr. Sylvain Letourneau

Transport Canada

Secretary Mr. Bob Hastings

Responsible To The DPHM Working Group Membership

AIAC Technology Council Chair.

Responsible For DPHM project team including and specifically for the technology implementation program support contractors and consultants.

Meeting Frequency The Steering Committee shall meet on an as required basis.

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Annex D to: Aircraft Systems Diagnostics, Prognostics and Health Management TID Aircraft DPHM Montreal Workshop Attendee List

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Annex D – Aircraft DPHM Montreal Workshop Attendee List

Surname First Name Company/Organization Phone Email Address

Abramovici Eugen Bombardier Aerospacep: (514) 855-2504f: (514) 855-2020

[email protected]

P.O. Box 6087, Station Centre-villeMontreal, Quebec H3C 3G9

Armstrong Jeff Bombardier [email protected]

P.O. Box 6087, Station Centre-villeMontreal, Quebec H3C 3G9

Atkinson BobIndustry Canada - Aerospace and Automotive Branch

p: (613) 954-3269f: (613) 952-8088 [email protected]

235 Queen StreetOttawa, Ontario K1A 0H5

Bird Jeff NRC-IAR Institute for Aerospace Research

p: (613) 993-2425f: (613) 957-3281 [email protected]

Montreal Road, Bldg M 50Ottawa, Ontario K1A 0R6

Brauss Michael Proto Manufacturing Ltd.p: (519) 737-6330f: (519) 737-1692 [email protected]

2175 Solar CrescentOldcastle, Ontario N0R 1L0

Castellano Jim Industry Canada - Aerospace and Automotive Branch

p: (613) 954-3747f: (613) 998-6703 [email protected]

235 Queen StreetOttawa, Ontario K1A 0H5

Cocorocchio Bruno Cocor Aero Products, Inc.p: (905) 415-2614f: (905) 415-2615 [email protected]

8 Blackwell CourtMarkham, Ontario L3R 0C2

D'Eon Phil CaseBank Technologiesp: (905) 792-0618 (x586)f: (905) 792-0446 [email protected]

1 Kenview BoulevardBrampton, Ontario L6T 5E6

Dionne Patrice Pratt & Whitney Canada p: (450) 647-7714 [email protected] Marie-Victorin (01LC4)Longueuil, Quebec J4G 1A1

Forester Dr. George NRC-IIT– Institute for Information Technology

p: (613) 993-3478f: (613) 952-0074 [email protected]

Montreal Road, Bldg M 50Ottawa, Ontario K1A 0R6

Gadher Bharat Life Prediction Technologies Inc.

p: (613) 744-7574f: (613) 744-5278

[email protected]

23 - 1010 Polytek StreetOttawa, Ontario K1J 9J1

Hastings Bob Pointman Canadap: (613) 859-6456f: (613) 737-3310 [email protected]

3063 Uplands DriveOttawa, Ontario K1V 9X7

Hosking Eric Pratt & Whitney Canadap: (450) 647-7336f: (450) 647-7441 [email protected]

1000 Marie-Victorin (01LC4)Longueuil, Quebec J4G 1A1

Jin Huitang (Hugh) Liburdi Engineering Ltd.p: (905) 689-0734f: (905) 589-0739 [email protected]

400 Hwy 6 NorthDundas, Ontario L9H 7K4

Koul Ashok Life Prediction Technologies Inc.

p: (613) 744-7574f: (613) 744-5278

[email protected]

23 - 1010 Polytek StreetOttawa, Ontario K1J 9J1

Lam Chun Ho Honeywell Canadap: (905) 608-6000 (x2495)f: (905) 608-6190

[email protected]

3333 Unity DriveMississauga, Ontario L5L 3S6

Langley Mark CaseBank Technologies Incp: (905) 792-0618 (x513)f: (905) 792-0446 [email protected]

1 Kenview BoulevardBrampton, Ontario L6T 5E6

Legault Michel Bell Helicoptersp: (450) 971-6500 (x6027)f: (450) 971-6039

[email protected]

12,800 rue de l'AvenirMirabel, Quebec J7J 1R4

Letourneau Dr. Sylvain NRC – IIT Institute for Information Technology

p: (613) 990-1178f: (613) 952-0215

[email protected]

1200 Montreal Road, Bldg M-50Ottawa, Ontario K1A 0R6

Li Dr. Ping Orenada Aerospacep: (613) 993-6464f: (613) 941-1329 [email protected]

1420 Blair Place, Suite 608Floucester, Ontario K1J 9L8

Lortie Michel DataCapture.ca Corporationp: (450 973-2240 (x1501)f: (450) 973-2259 [email protected]

560 Cartier Blvd. WestLaval, Quebec H7V 1J1

Louwet Lucie Pratt & Whitney Canadap: (450) 647-4075f: (450) 647-2888 [email protected]

1000 Marie-Victorin (01LC4)Longueuil, Quebec J4G 1A1

McRae Ken DND-HAVRS Air Vehicles Sector

p: (613) 991-6908f: (613) 993-4095

[email protected]

National Defence HeadquartersOttawa, Ontario K1A 0K2

Moustapha Hany Pratt & Whitney Canadap: (450) 647-7593f: (450) 647-3394 [email protected]

1000 Marie-Victorin (01LC4)Longueuil, Quebec J4G 1A1

Mrad NezihDND - AVRS Air VehiclesResearch Section

p: (613) 993-6443f: (613) 993-4095

[email protected]

National Defence HeadquartersOttawa, Ontario K1A 0K2

Muir Dave GasTOPS Ltd.p: (613) 744-3530f: (613) 744-8846 [email protected]

1011Polytek StreetOttawa, Ontario K1J 9J3

Nguyen Phuc Pratt & Whitney Canadap: (450) 647-2869f: (45) 647-2888

[email protected]

1000 Marie-Victorin (01LC4)Longueuil, Quebec J4G 1A1

Oakland David Howell Instrumentsp: (516) 791-1000/1001f: ( 516) 791-6761 [email protected]

181 S. Franklin Ave. #307Valley Stream, N.Y. 11581

Oxorn Kenneth Atlantic Nuclear Services Ltd.p: (514) 343-7669f: (514) 343-6215 [email protected]

P.O. Box 6128, Station CVMontreal, Quebec H3C 3J7

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Surname First Name Company/Organization Phone Email Address

Pagnotta Vince Pratt & Whitney Canadap: (450) 468-7885f: (450) 468-7908 [email protected]

1000 Marie-Victorin (01LC4)Longueuil, Quebec J4G 1A1

Paquette Michel Bombardier Aerospace

p: (514) 855-5000(x55053)f: (514) 855-7207

[email protected]

P.O. Box 6087, Station Centre-villeMontreal, Quebec H3C 3G9

Peloso Dave MXI Technologiesp: (613) 747-4698 (x207)f: (613) 747-1909 [email protected]

1430 Blair Place, Suite 800Ottawa, Ontario K1J 9N2

Remy Patrice Pratt & Whitney Canada p: (450) 677-9411 (x5034) [email protected] Marie-Victorin (01LC4)Longueuil, Quebec J4G 1A1

Stiharu Ion Concordia Universityp: (514) 848-3152f: (514) 848-3175 [email protected]

1455 de Maisonneuve Blvd WMontreal, Quebec H3G 1M8

Thomas Wayne Standard Aero Ltd.p: (204) 775-9711f: (204) 788-2168

[email protected]

33 Allen Dyne RoadWinnipeg, Manitoba R3H 1A1

Trindade Carlos Bombardier Aerospacep: (514) 855-5000f: (514) 855-7302

[email protected]

P.O. Box 6087, Station Centre-villeMontreal, Quebec H3C 3G9

Watson Peter Altairp: (802) 238-3129f: (802) 288-9442

[email protected]

63 Nahatan Street, Suite 300Norwood, MA 02062

Yang Dr. Chunsheng NRC -IIT - Institute for Information Technology

p: (613) 991-5499f: (613) 952-0215 [email protected]

1500 Montreal Road, Bldg M 50Ottawa, Ontario K1A 0R6

Zaluski MarvinNRC –IIT - Institute for Information Technology

p: (613) 998-0071f: (613) 952-7151 [email protected]

Montreal Road, Bldg M 50Ottawa, Ontario K1A 0R6

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Annex E to: Aircraft Systems Diagnostics, Prognostics and Health Management TID Aircraft DPHM Ottawa Workshop Attendee List

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Annex E – Aircraft DPHM Ottawa Workshop Attendee List

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Surname First Name Company/Organization Phone Number Email AddressAnnis Richard Industry Canada TPC 613-954-9869 [email protected] Bob Industry Canada 613-954-3269 [email protected] Michael Bell Helicopters 817-280-8719 [email protected] Wieslaw NRC - IAR (613) 993-0033 [email protected] Bird Jeff NRC - IAR 613-993-2425 [email protected] Ghislain DND - QETE 819-994-6538 [email protected] Greg Industry Canada 613-954-3266 [email protected] Jeff Mxi 613-747-4698 (203) [email protected] Jim Industry Canada (613) 954-3747 [email protected] Iain Neptec 613-599-7603 x 254 [email protected] Dave DND - QETE 613-997-9107 [email protected] Georges Atlantic Nuclear Services Ltd 506-458-9552 [email protected] Curran-Allen Hilary Industry Canada (613) 941-5567 [email protected] Azzedine NRC - IAR 613- 991-9529 [email protected]'Eon Phil CaseBank Technologies (905) 792-0618 Ext586 [email protected] Roop Transport Canada 613-941-7470 [email protected] Bartolomeo Walter Pratt & Whitney Canada 450-647-7695 [email protected] Patrice Pratt & Whitney Canada (450) 647-7714 [email protected] Waldek. NRC-IAR 613-990-0457 [email protected] Chris NRC-IIT 613 993-0709 [email protected] Eastaugh Graeme NRC - IAR 613 993-2845 [email protected] Abbas NRC - IAR (613) 993-5258 [email protected] Fews Robert Bell Helicopters (450) 437-3400 ext 2789 [email protected] George NRC - IIT (613) 993-3478 [email protected] Arnold MAYA Metrix (514) 369-5706 [email protected] Dan LPTI (613) 744-7574 [email protected] Bharat K LPTI (613) 744-7574 [email protected] Armineh GlobVision Inc. (514) 855-0455 [email protected] Marc NRC- IAR 613-949-1326 [email protected] Bob PointMan Canada Ltd 613-737-3310 [email protected] Jim Standard Aero Limited (210) 334-6161 [email protected] Ken NRC-IRAP 613 991-4425 [email protected] Andreas HRSDC 819-997-4175 [email protected] Eric Pratt & Whitney Canada (450) 647-7336 [email protected] Farzan CRA - SREDs (613) 957-9399 [email protected]

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Surname First Name Company/Organization Phone Number Email AddressKane Ron AIAC 613-232-4297 [email protected] Thanos Aerosoft PMI Systems 905-678-9564 [email protected] Hanna CRA SR&ED R&T Advisor 514 496-1878 [email protected] Peter Honeywell (905) 608-6025 [email protected] Jerzy NRC - IAR (613) 993-3999 [email protected] Marc MAYA Metrix (800) 343-6292 Ext 283 [email protected] Chun Ho Honeywell (905) 608-6000 (x2495) [email protected] Sylvain NRC - IIT (613) 990-1178 [email protected] Lucie Pratt & Whitney Canada (450) 647-4075 [email protected] Patrice Universite de Sherbrooke 819-821-8000 ext 2152 [email protected] Ken DND - H/AVRS (613) 991-6908 [email protected]énard Jean Bombardier 450-476-7315 [email protected] Philippe Universite de Sherbrooke 819-821-8000 ext 2161 [email protected] Hany Pratt & Whitney Canada (450) 647-7593 [email protected] Nezih DND - AVRS (613) 993-6443 [email protected] Dave GasTOPS Ltd (613) 744-3530 [email protected] Jeff GasTOPS Ltd (613) 744-3530 [email protected] Phuc L. Pratt & Whitney Canada 450-647-2869 [email protected] Larry Industry Canada TPC (613) 941-5607 [email protected] Don MDS Aero Support 613-744-7257 [email protected] Pierre Bell Helicopters 450-971-6500 ext 6867 [email protected] Piotr CRA, BD Montreal 514-496-5720 [email protected] Nirmal K. NRC-IAR (613) 990-0650 [email protected] Sixto Roger Aerosoft PMI Systems 954-447-7200 , ext 693 [email protected] Christine Neptec 613-599-7602 [email protected] Ion Concordia University 514-848-2424 ext 3152 [email protected] Andy Transport Canada (613) 952-4335 [email protected] Martin Industry Canada (613) 954-3166 [email protected] Captain Darryl DND - DAEPM(TH) (613) 991-9642 [email protected] Graham Precarn 613-727-9507 ext 230 [email protected] Peter NRC - IAR (613) 993-7929 [email protected] Louis-Michel Pratt & Whitney Canada 450-647-2700 [email protected] Xijia NRC - IAR (613) 990-5051 [email protected] Chunsheng NRC - IIT 613 991-5499 [email protected] Marko NRC-IAR 613 991-6926 [email protected] Marvin NRC - IIT 613 998-0071 [email protected]

18 November 2004 Ottawa - DPHM Workshop Attendance List