5 8 A S H R A E J o u r n a l a s h r a e . o r g A p r i l 2 0 0 3

System & Component DiagnosticsBy Detlef Westphalen, Ph.D., Member ASHRAE, Kurt W. Roth, Associate Member ASHRAE,

and James Brodrick, Ph.D., Member ASHRAE

agnostics depends on the frequency and severity of major faultmodes in typical equipment and the extent to which the diag-nostic systems would eliminate or reduce operation in faultmodes. At present, accurate information allowing such an esti-mate is not publicly available.

A handful of engineers and contractors interviewed aboutdiagnostics suggest that the energy wasted by inefficient op-eration likely equals at least 20% to 30% of HVAC energy con-sumption. The principal of a company that performs energyconservation studies and designs energy improvements for com-mercial buildings said that improper equipment operation, poorinstallation, etc., are responsible for more than 20% of HVACenergy consumption. In his experience, low-cost measures tomake equipment and systems operate properly rather thancapital-intensive improvements account for most of the en-ergy savings that he has identified during his 20-year career.1

In particular, diagnostics offer substantial energy savingspotential for packaged rooftop units, which appear to havehigh fault rates. One engineer suggested that more than 50%of packaged rooftop units are not operating properly,2 while arecent study found that most economizers do not functionproperly.3 Another (two-year) study of the energy and demandimpacts of maintenance on packaged rooftop equipment4 foundthat problems due to improper system installation did have asignificant negative impact, while maintenance-related items,e.g., improper refrigerant charge and air filter change frequency,had little energy impact. Table 2 summarizes the range of en-ergy impact that could be attributed to different fault modesfor unitary air conditioners.5

On a whole-building scale, Claridge et al.6 measured sav-ings of 14% to 33% for several medical office buildings witha simple payback period (SPP) averaging about a year usingwhole building diagnostics (WBD).

Market FactorsA range of implementation scenarios can be conceived for

system diagnostics for HVAC equipment, but the most promis-ing approaches from the standpoints of successful operationand marketplace acceptance remain unclear. The lowest costapproach is to integrate diagnostic capability into a systemselectronic controls, a standard practice for some HVAC equip-ment (e.g., centrifugal chillers).

Even if diagnostics capability is integrated with equip-ment controllers, it requires greater sophistication to addressHVAC system operational faults, since systems incorporate arange of equipment types. Applying diagnostics to equip-

This is the second article covering one of several new en-ergy-saving technologies evaluated in a recent U.S. Depart-ment of Energy report. The complete report is atwww.eren.doe.gov/buildings/documents.

ystem diagnostics can be used to automatically identifyoperation failures of HVAC equipment and systems. Ifsuch systems can identify inefficient system performance

and alert building operators, the systems can be fixed sooner,thus reducing the time of operating inefficiently or in failuremodes, thus saving energy.

A range of diagnostic systems have been proposed, re-searched, developed, and/or commercialized for detection offaults in commercial HVAC equipment and systems. The com-mon thread in all of these systems is monitoring of equipmentto determine whether it is operating properly or needs service.Some examples include:

1. Electronic controllers programmed for maximum and mini-mum values of key control parameters, with notification ofalarm conditions.

2. Algorithms integrated into electronic controllers, or add-onsystems incorporating sensors and electronic processors, that col-lect operating data and analyze equipment operating parameters.

3. Facilities connected to building energy management sys-tems (BEMS) that monitor key operating parameters of majorequipment to ensure proper equipment operation. Variationsinclude easily viewable graphic displays, plotting of datatrends, comparison of actual and modeled building operation.

4. Computer programs that actively analyze building operat-ing data from a BEMS to spot possible equipment malfunctions.

5. Enhanced communications interfaces to improve accessto data, including: BACnet and other approaches tointeroperability of building equipment controls, private net-works linking buildings to central management locations, andwireless communications.

Table 1 offers some illustrative examples of the consider-able work that has gone into developing HVAC diagnostics,but is by no means exhaustive.

Energy Savings PotentialAlthough the literature reports few good estimates of energy

savings resulting from the use of automatic diagnostics, ex-tensive anecdotal evidence exists regarding the number ofimproperly operating HVAC systems. Similarly, there are sev-eral specific examples of diagnostics applied to simulatedequipment failures. The energy savings potential of HVAC di-

S

The following article was published in ASHRAE Journal, April 2003. Copyright 2003 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. It is presented for educational purposes only. This article may not be copied and/or distributed electronically or inpaper form without permission of ASHRAE.

A p r i l 2 0 0 3 ASHRAE Journa l 5 9

EquipmentType Faults Diagnosis Approach

AHU Heat Exchanger Fouling Valve Leakage

Comparison of Modelsand Actual Performance7

Comparison ofOperation with a Fuzzy

Model8

VAV AHU

Return Fan FailureSupply Fan FailureCHW Pump FailureCHW Valve StuckSensor FailurePressure Sensor FailureOthers

Residual Method andParameter IdentificationMethod (using ARMAX

and ARX models)9

Artificial NeuralNetworks10

VAV AHU VAV Damper Stuck ARX Models ExtendedKalman Filter11

Water-Cooled

Reciprocati-ng Chiller

Refrigerant Leak LiquidLine RestrictionCW Flow ReductionCHW Flow Reduction

Modeling, PatternRecognition, Expert

Knowledge12

AbsorptionChiller COP Degradation

Topological Case-BasedMonitoring13

Unitary Air-Conditioner

Refrigerant LeakCompressor Valve LeakLiquid Line RestrictionCondenser FoulingEvaporator Fouling

Statistical Analysis ofResiduals of Modeled vs.

Actual OperatingParameters14

HVAC,Lighting,

etc.

A Range of BuildingOperational Problems,also Including IncorrectBilling

Whole BuildingDiagnostics6, 15, 16

ARMAX: Autoregressive moving average with exogenour input; ARX: Auto-regressive with exogenous input; CHW: chilled water; CW: condenser water

ment without electronic control requires add-on systems con-sisting of sensors, communications interfaces, and micropro-cessors, thereby increasing costs.

It is difficult to quantify the benefit of automated systemdiagnostics, as the rate and level of faults in actual equipmentvaries significantly from one unit to another, creating a broadrange of SPPs. TIAX developed two estimates for the installa-tion cost and economics of system diagnostics for a rooftopunit serving a fast food restaurant. It found that the SPP rangedfrom under a year to three years, with more complex systemshaving a longer SPP.5

Several non-economic market barriers have impeded the adop-tion of system diagnostics in the HVAC industry. In general, theuse of electronic controls is increasing but not yet dominant formany equipment types. Hence, using all but the simplest diag-nostic approaches requires separate systems, increasing systemcost and complexity. In addition, many stakeholders do notrecognize a need for automated diagnostics.

References1. Donahue, J.L. 2001. Personal Communication, Energy Planning.2. Shapiro, A. 2001. Personal Communication, Taitem Engineering.3. Energy Design Resources. 2002. Economizers design brief.

www.energydesignresources.com/publications/design_briefs/pdfs/VOL_02/DB-Economizers.pdf.

4. EPRI. 1997. The impact of maintenance on packaged unitaryequipment. EPRI Report TR-107273, abstract at www.epri.com/OrderableitemDesc.asp?product_id=TR-107273.

5. TIAX. 2002. Energy Consumption Characteristics of CommercialBuilding HVAC Systems Volume III: Energy Savings Potential. FinalReport to U.S. DOE, Office of Building Technologies, July.

6. Claridge, D., M. Liu, and W.D. Turner. 1999. Whole Building Diag-nostics Workshop. http://poet.lbl.gov/diagworkshop/proceedings/.

7. Haves, P., T.I. Salsbury, J.A. Wright. 1996. Condition monitoringin HVAC subsystems using first principles models. ASHRAE TechnicalData Bulletin (12)2.

8. Dexter, A.L. and M. Benouarets. 1996. A generic approach to identi-fying faults in HVAC plants. ASHRAE Technical Data Bulletin 12(2).

9. Lee, W.Y., C. Park, G.E. Kelly. 1996a. Fault detection in an air-handling unit using residual and recursive parameter identification meth-ods. ASHRAE Technical Data Bulletin (12)2.

10. Lee, W.Y., et al. 1996b. Fault diagnosis of an air-handling unitusing artificial neural networks. ASHRAE Technical Data Bulletin (12)2.

11. Yoshida, H., et al. 1996. Typical faults of air-conditioning sys-tems and detection by ARX and extended Kalman filter. ASHRAE Tech-nical Data Bulletin (12)2.

12. Stylianou, M. and D. Nikanpour. 1996. Performance monitoring,fault detection, and diagnosis of reciprocating chillers. ASHRAE Techni-cal Data Bulletin (12)2.

13. Tsutsui, H. and K. Kamimura. 1996. Chiller condition monitor-ing using topological case-based monitoring. ASHRAE Technical DataBulletin (12)2.

14. Rossi, T.M. and J.E. Braun. 1997. A statistical, rule-based faultdetection and diagnostic method for vapor compression air condition-ers. International Journal of HVAC&R Research 3(1).

15. Santos, J.J., E.L. Brightbill, and L. Lister. 2000. Automated diag-nostics from DDC data PACRAT. Proceedings of the National Confer-ence on Building.

16. Piette, M.A., S. Khalsa and P. Haves. 2000. Use of an informationmonitoring and diagnostic system for commissioning and ongoing op-erations. Proceedings of the National Conference on Building Commis-sioning.

17. Breuker, M., T. Rossi, J. Braun. 2000. Smart maintenance forrooftop units. ASHRAE Journal 42(11):4147.

Detlef Westphalen, Ph.D. is a senior manager, HVAC/R group.Kurt W. Roth is a project manager with TIAX in Cambridge,Mass. James Brodrick, Ph.D. is a project manager, Building Tech-nologies Program, U.S. Department of Energy, Washington, D.C.

Fault Mode Potential Increasein Energy Use

Refrigerant Leakage (15% of Design Charge)17 5.0%*Liquid Line Restriction (15% Increase in

Pressure Drop)17 5.0%

Compressor Valve Leak (15% decrease inVolumetric Efficiency)17 11.0%

Condenser Fouling (30% of Face Area)17 8.0%Evaporator Fouling (25% Reduction in Airflow)17 12.5%

Improper Control Resulting in Overcooling5 20.0%No Economizing5 10.0%

Failure to Switch to Minimum Outdoor AirSetting in Summer5 10.0%

Operation at Night5 20.0%Condenser Fan/Motor Failure5 15.0%

* EPRI (1997) reported a negligible impact on energy use.

Table 1: Common faults and diagnostic methods.5

Table 2: Estimated increase in cooling energy use for unitaryequipment for possible fault modes.5