Evaluation of the suitability of different chiller performance models for on-line training applied to automated fault detection and diagnosis (RP-1139)

HVAC and R Research

Volumn 9, Issue 4, 2003, Pages 385-414

  Reddy, T Agami ^a   Niebur, Dagmar ^a   Andersen, Klaus K ^c   Pericolo, Paolo P ^a   Cabrera, Gaspar ^b  

^a Architectural and Environmental Engineering ^*  (United States)

^b Drexel University   (United States)

^c TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

AIR CONDITIONING; CORRELATION METHODS; ERROR ANALYSIS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; MULTILAYER NEURAL NETWORKS; ONLINE SYSTEMS; PARAMETER ESTIMATION; POLYNOMIAL APPROXIMATION; RADIAL BASIS FUNCTION NETWORKS; RECURSIVE FUNCTIONS; SPACE HEATING; VENTILATION;

CHILLER SYSTEMS; FAULT DETECTION;

COOLING SYSTEMS;

EID: 0344826836     PISSN: 10789669     EISSN: None     Source Type: Journal    
DOI: 10.1080/10789669.2003.10391077     Document Type: Article

References (42)

1. Box, G. E. P., and Jenkins, G. M., 1976. Time Series Analysis, Forecasting and Control. San Francisco:Holden-Day.
2. Box, G., and Luceno, A., 1997. Statistical Control by Monitoring and Feedback Adjustment. New York:Wiley Interscience.
3. Braun, J. E., 1988. Methodologies for the design and control of central cooling plants, Ph.D dissertation Mechanical Engineering Department, University of Wisconsin-Madison.
4. Braun, J. E., and Chaturvedi, N., 2002. An inverse gray-model for transient building load prediction. HVAC&R Research, 8 (1):73–99.
5. Chatfield, C., 1984. The Analysis of Time Series, 4th ed. London:Chapman and Hall.
6. Chen, J., and Patton, R. J., 1999. Robust Model-Based Fault Diagnosis for Dynamic Systems. Boston:Kluwer Academic Publishers.
7. Comstock, M. C., Chen, B., and Braun, J. E., 1999. Literature review for application of fault detection and diagnostic methods to vapor compression cooling equipment Ray Herrick Laboratories, Purdue University. HL 99–19, Report #4036–2, December
8. Comstock, M. C., and Braun, J. E., 1999. Development of Analysis Tools for the Evaluation of Fault Detection and Diagnostics in Chillers Ray Herrick Laboratories, Purdue University. HL 99–20, Report #4036–3, December
9. Corcoran, J. P., and Reddy, T. A., 2003. Improving the process of certified and witnessed factory testing for chiller procurement. ASHRAE Transactions, 109 (1)
10. DOE. 1981. DOE-2, Reference Manual, Part 1, Version 2.1 Berkeley, Calif:Lawrence Berkeley National Laboratory.
11. Draper, N., and Smith, H., 1981. Applied Regression Analysis, 2d ed. New York:John Wiley & Sons.
12. Gertler, J. J., 1998. Fault Detection and Diagnosis in Engineering Systems. New York:Marcel Dekker.
13. Gordon, J. M., and Ng, K. C., 2000. Cool Thermodynamics. Cambridge:Cambridge Press.
14. Haykin, S., 1999. Neural Networks:A Comprehensive Foundation, 2d ed. Upper Saddle River, N. J.:Prentice Hall.
15. Himmelblau, D. M., 1978. Fault Detection and Diagnosis in Chemical and Petrochemical Processes Elsevier. Chemical Engineering Monograph 8
16. Hsia, T. C., 1977. System Identification:Least-Squares Method. Lexington:Lexington Books.
17. Hyvarinen, J., and Karki, S., eds. 1996. International Energy Agency Building Optimisation and Fault Diagnosis Source Book. Laboratory of Heating and Ventilation. Published by the Technical Research Center of Finland
18. Isermann, R., Baur, U., Bamberger, W., Kneppo, P., and Siebert, H., 1974. Comparison of six on-line identification and parameter estimation methods. Automatica, 10:81
19. Jia, Y., and Reddy, T. A., 2003. The characteristic physical parameter approach to modeling chillers suitable for fault detection, diagnosis and evaluation. ASME Journal of Solar Energy Engineering, Vol. 125 (3) August
20. Jiang, W., and Reddy, T. A., 2003. Re-evaluation of the Gordon-Ng performance models for water-cooled chillers. ASHRAE Transactions, 109 (2)
21. Katipamula, S., Pratt, R. G., and Braun, J. E., 2001. “ Building systems diagnostics and predictive maintenance, Chapter 7.2. ”. In CRC Handbook for HVAC&R Engineers Edited by:Kreider, J., CRC Press.
22. Ljung, L., 1999. System Identification, Theory for the User. Prentice Hall.
23. Mangoubi, R. S., 1998. Robust Estimation and Failure Detection. Springer:Advances in Industrial Control.
24. Ngia, L. S. H., and Sjoberg, J., 2000. Efficient training of neural nets for nonlinear adaptive filtering using a recursive Levenberg-Marquardt algorithm. IEEE Transactions on Signal Processing, 48 (7):1915–1927.
25. Niebur, D., and Dillon, T., 1996. “ State of the art. ”. In Neural Net Applications in Power Systems Edited by:Dillon, T., and Niebur, D., 37–110. Leics, U. K.:CRL Publishing Ltd.
26. Obradovic, D., 1996. On-line training of recurrent neural networks with continuous topology adaptation. IEEE Transactions on Neural Networks, 7 (1):222–228.
27. Patton, R., Frank, P., and Clark, R., eds. 1989. Fault Diagnosis in Dynamic Systems:Theory and Applications. New York:Prentice-Hall.
28. Pau, L. F., 1975. Failure Diagnosis and Performance Monitoring. New York:Marcel Dekker.
29. Pericolo, P. P., Niebur, D., and Reddy, T. A., 2002. Comparison of chiller performance models, Submitted to the IEEE Transactions on Industrial Electronics August
30. Pericolo, Paolo Pietro. 2001. Supervised artificial neural networks for monitoring the performance of chillers, MS thesis Drexel University. July
31. Pouliezos, A. D., and Stravrakakis, G. S., 1994. Real-Time Fault Monitoring of Industrial Processes. Dordrecht:Kluwer Academic Publishers.
32. Reddy, T. A., Kissock, J. K., and Ruch, D. K., 1998. Uncertainty in baseline regression modeling and in determination of retrofit savings. Journal of Solar Energy Eng., Vol. 120:185 August
33. Reddy, T. A., Elleson, J. S., and Haberl, J. S., 2001a. Final Report:Determining long-term performance of cool storage systems from short-term tests ASHRAE Research Project 1004-RP, Atlanta, Ga., January
34. Reddy, T. A., Niebur, D., Gordon, J., Seem, J., Andersen, K., Cabrera, G., Jia, Y., and Pericolo, P., 2001b. Final Report:Development and comparison of on-line model training techniques for model-based FDD methods applied to vapor compression chillers ASHRAE Research Project 1139-RP, September
35. Reddy, T. A., and Andersen, K. K., 2002. An evaluation of classical steady-state off-line linear parameter estimation methods applied to chiller performance data. HVAC&R Research Journal, 8 (1):101
36. Reddy, T. A., Andersen, K. K., and Niebur, D., 2003. Information content of incoming data during field monitoring:Application to chiller modeling. HVAC&R Research Journal, 9 (4)
37. Saridis, G. N., 1974. Comparison of six on-line identification algorithms. Automatica, Vol. 10:69
38. Sinha, N. K., and Sen, A., 1975. Critical evaluation of online identification methods. Proceedings of the IEE- Control and Science, 122 (10):1153 October
39. Sinha, N. K., and Kuszta, B., 1983. Modeling and Identification of Dynamic Systems van Nostrand Rein-hold Electrical/Computer Science and Engineering Series.
40. Sreedharan, P., and Haves, P., Comparison of chiller models for use in model-based fault detection. International Conference for Enhanced Building Operations (ICEBO), organized by Texas A&M University. July, Austin, Texas.
41. Wen, J., and Smith, T. F., 2003. Development and validation of online parameter estimation for HVAC systems. ASME Journal of Solar Energy Engineering, Vol. 125 (3) August
42. Zaheer-uddin, M., 1990. Combined energy balance and recursive methods applied to a single-zone HVAC system. ASHRAE Transactions, 93 (1):1814