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AN INTRODUCTION TO FAULTDIAGNOSIS SYSTEMDr. Jafar ZareiShiraz University of Technology

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Fault Diagnosis System

CONTENTS

¢ Introduction to Process Automation¢Definition ¢Classification of Faults¢Fault Detection Methodó Signal Model-Based Fault Detectionó Model-Based Fault Detectionó Knowledge- Based

¢Historical notes¢Course Outline

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PROCESS AUTOMATION AND PROCESSSUPERVISION

ó With the improvement of lower control functions the supervision functions must be improved 3

Sequential control, feedforward and feedback control

Coordination, optimization, and management

FAULT APPEARANCE

¢ There are many reasons for the appearance of faultsó wrong design, wrong assemblingó wrong operation, missing maintenanceó ageing, corrosion, wear during normal operation

¢ In the past: Limit checking of some important process variables.ó Faults are detected rather latelyó Detailed fault diagnosis in mostly not possible with

simple methods

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THE GOAL OF MODERN FAULT DETECTIONMETHODS

¢ Early detection of small faults with abrupt or incipient behavior

¢ Diagnosis of faults in actuators, processes, components and sensors; fault detection in closed loops;

¢ Supervision of process in transient states;¢ Process condition-based maintenance and repair;¢ Deep quality control of assembled products in

manufacturing;¢ Teleservices like remote fault detection and diagnosis;¢ Basis for fault management;¢ Basis for fault-tolerant and reconfigurable systems. 5

WHY FAULT DETECTION IS NEEDED?

¢ USAir Flight 427 accident ¢ USA Flight 585 accident

Crashed on 8 Sept. 1994A loss of control of the airplane resulting fromthe movement of the rudder surface to itsblowdown limit, which leads to anuncontrolled descent and collision with terrainAll 132 people on board were killed, and theairplane was destroyed by impact forces andfire.

Crashed on 3 March 1991A loss of control of the airplane resulting from the movement of the rudder surface to itsblowdown limit, the same reason as in Flight427.Injuries: 25 Fatal; The airplane was destroyed.

Motivation for Fault Tolerant Control Systems Research & Development

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TWO EVENTS CALLED FOR RESEARCH ONFAULT TOLERANT CONTROL SYSTEMS

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¢ Crashed on 25 May 1979¢ Separation of the no.1 engine and

pylon assembly procedures which led to failure of the pylon structure.

¢ 271 people were killed/injured.

¢ Safely landed on 12 April 1977¢ The elevator became jammed at 19

degrees up and the pilot had been given no indication that this malfunction had occurred.

¢ Fortunately, the pilot successfully reconfigured the remaining control elements and landed the aircraft safely - clever use of actuation

Flight 191 accident – failed case Flight 1080 – successful exampleTwo events that motivated the research on fault-tolerant flight control

DEFINITION: STATES ANDSIGNALS

What is a fault?

ó Fault: Unpermitted deviation of at least one characteristic property of the system;

ó Failure: Permanent interruption of a systems ability to perform a required function under specified operating conditions;

ó Malfunction: Intermittent irregularity in fulfillment of a systems desired function

ó Error: Deviation between a computed value (of an output variable) and the true, specified or theoretically correct value;

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DEFINITION: STATES ANDSIGNALSó Disturbance: An unknown (and uncontrolled) input acting

on a system

ó Perturbation: An input acting on a system which results in a temporary departure from current state

ó Residual: Fault indicator, based on deviation between measurements and model-equation-based computations

ó Symptom: Change of an observable quantity from normal behavior

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DEFINITION: FUNCTION

ó Fault Detection: Determination of faults present in a system and time of detection;

ó Fault Isolation: Determination of kind, location and time of detection of a fault by evaluating symptoms. Follows fault detection;

ó Fault Identification: Determination of the size and time-variant behavior of a fault. Follows fault isolation;

ó Fault Diagnosis: Determination of kind, size, location and time of detection of a fault by evaluating symptoms. Follows fault detection. Includes fault detection, isolation and identification;

ó Monitoring: A continuous real-time task of determining the possible conditions of a physical system, recognizing and indicating anomalies of the behavior;

ó Supervision: Monitoring a physical system and taking appropriate actions to maintain the operation in the case of faults

ó Protection: Means by which a potentially dangerous behavior of the system is suppressed if possible, or means by which the consequences of a dangerous behavior are avoided

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DEFINITION: MODELSó Quantitative model: Use of static and dynamic

relations among system variables and parameters in order to describe systems behavior in quantitative mathematical terms

ó Qualitative model: Use of static and dynamic relations among system variables and parameters in order to describe systems behavior in qualitative terms such as causalities or if-then rules

ó Diagnostic model: A set of static or dynamic relations which link specific input variables - the symptoms -to specific output variables - the faults

ó Analytical redundancy: Use of two or more, but not necessarily identical ways to determine a variable where one way uses a mathematical process model in analytical form 11

DEFINITION: SYSTEM PROPERTIESó Reliability: Ability of a system to perform a required

function under stated conditions, within a given scope, during a given period of time. Measure: MTBF = Mean Time Between Failure. MTBF = 1\la; la is rate of failure [e.g. failures per year]

ó Safety: Ability of a system not to cause a danger for persons or equipment or environment

ó Availability: Probability that a system or equipment will operate satisfactorily and effectively at any point of time measure: MTTR: Mean Time To Repair MTTR = 1/µ; µ: rate of repair

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TASK OF A FAULT DETECTION SYSTEM

¢ Fault Detection¢ Fault Isolation¢ Fault Identification

¢ Fault Detection and Isolation FDI¢ Fault Detection and Diagnosis FDD

¢ Objectives: Increase reliability, safety andautomation level of modern technological/engineering systems 13

CLASSIFICATION OF FAULTS

¢ Based on Time Behavioró Abrupt Fault (stepwise)

¢ Total failure of a component¢ Caused by, for example, short-

circuits or melt-down¢ Remains until component is

repaired or replacedó Incipient Fault (drift-like)ó Intermittent Fault (with

interrupts)¢ Repeated occurrences of transient

faults¢ Caused by, for example, loose

wires

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CLASSIFICATION OF FAULTS

¢ Based on Locationó Sensor Faults ó Actuator Faultsó Process (Components)

Faults¢ Based on Process

Modelsó Multiplicative Faultsó Additive Faults

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FAULT DETECTION METHODS

¢ Classical Methodó Hardware Redundancyó Limit Checking

¢ Signal Model- Based Fault Detection¢ Model- Based Fault Detection¢ Knowledge- Based Fault Detection

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HARDWARE REDUNDANCY

¢Static Redundancy

¢Dynamic Redundancy

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HARDWARE REDUNDANCY EXAMPLE

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Actuator servo-drive for cabin pressure control

Redundant DC motor drive system for the outflow valve

Fault diagnosis of a cabin pressure outflow valve actuator of a passenger aircraft

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FAULT DETECTION WITH LIMIT CHECKING

¢ Limit checking of absolute values

¢ Trend checking

¢ Change detection with binary thresholds

¢ Change detection with fuzzy thresholds

¢ Adaptive thresholds

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SCHEME OF FAULT DETECTION WITH SIGNALMODEL

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SCHEME OF MODEL-BASE FAULTDETECTION

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WHERE DOES THE FTCS STAND?Fault Detection and Diagnosis (FDD)

Optimal, Adaptive,Robust Control(Reliable Control orPassive FTCS)

Computing, Communication,

Simulation,Implementation

(hardware/software),and Display Techniques

Reconfigurable/Restructurable Control

Questions:• What are difference between active fault tolerant control and adaptive control, robust control and reliable control?

Active FTCS(a currently activeresearch area)

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ENGINEERING APPLICATION AREAS OF FDI¢ Engineering Application Areas of FDI

ó – Aircraft/Aerospace systemsó – Ground and surface/underwater vehiclesó – Nuclear reactors and power plantsó – Chemical/Petrochemical processesó – Autonomous robots and vehiclesó – Medical devices etc.

¢ Typical Faults Considered in FDIó – Actuator faultsó – Sensor faultsó – Structural/Dynamic faults

¢ Safety Criteriaó – Reliability, maintainability, and safety

¢ Requirement on Fault Diagnosis and Fault-Tolerant Controló – Fault diagnosisó – Fault-tolerant control 23

SIGNAL FLOW FOR FAULT DETECTION, FAULT DIAGNOSIS AND FAULTMANAGEMENT AND PICTURES OF SOME ACTUATORS, PROCESSES AND SENSORS

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HISTORICAL NOTES

¢ 19th century Limit checking, ¢ Since 1935 Ink and Point printing recorder¢ Around 1960 Analogue controllers with transistor

based amplifier¢ 1960 implementation of on-line process computer¢ 1968 First programmable logic controller were

introduced¢ 1971 advent of microcomputer and its application

in decentralized process automation ¢ since 1975 software-based supervision and fault

detection algorithm¢ First application on process model-based fault

detection methods appeared in connection with aerospace system, and chemical plants 25

COURSE OUTLINE1. Introduction, Background, Fault Detection, Fault Isolation, Fault Identification, Fundamental, Aims and basic concepts of process diagnostic, main categories of fault diagnosis.

2. Fault Detection,a. Signal based Fault detectionb. Model based Fault detection

i. Fault delectability and its conditionii. Residual, its properties and types, residual

generation, residual evaluation,iii. Parameter estimation methods, least square

parameter estimation family,iv. State estimation methods, parity space approach,

factorization approach: H-infinity and H2 optimization, observer based approach, deterministic: fault detection filter, hierarchical observers, stochastic case Kalman filter, actuators components and sensor fault detection. 26

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COURSE OUTLINE

Fault Isolation,a. Fault isolability and its condition,b. Sensor and actuator faults isolation4. Robust residual generation via UIOs

5. Fault diagnosis of non-linear dynamic systems

6. Modern Techniques:-Pattern recognition methods- Fuzzy logic approach, Fault isolation by fuzzy neural network models, fault isolation with use of fuzzy logic: fuzzy evaluation of residual, rules of inference, …- Neural network approaches 27

REFERENCES

¢ 1- R. Isermann, Fault-Diagnosis Systems an Introduction from Fault Detection to Fault Tolerance, Springer-Verlag Berlin Heidelberg, 2006.

¢ 2- J. Chen and R. J. Patton, Robust model-based fault diagnosis for dynamic systems, Massachusetts, Kluwer Academic Publishers, 1999.

¢ S. X. Ding, Model-based Fault Diagnosis Techniques,Springer, 2007.

¢ 3- M. Blanke and others, Diagnosis and Fault Tolerant Control, Springer, 2006.

¢ 4- Marcin Witczak, Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear System: From Analytical to Soft Computing Approaches, 2007. 28