Characteristic physical parameter approach to modeling chillers suitable for fault detection, diagnosis, and evaluation

Yongzhong Jia, T Agami Reddy

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

Model-based fault detection and diagnosis approaches based on statistical models for fault-free performance concurrently require a fault classifier database for diagnosis. On the other hand, a model with physical parameters would directly provide such diagnostic ability. In this paper, we propose a generic model development approach, called the characteristic parameter approach, which is suitable for large engineering systems that usually come equipped with numerous sensors. Such an approach is applied to large centrifugal chillers, which are generally the single most expensive piece of equipment in heating, ventilating, air-conditioning, and refrigeration systems. The basis of the characteristic parameter approach is to quantify the performance of each and every primary component of the chiller (the electrical motor, the compressor, the condenser heat exchanger, the evaporator heat exchanger, and the expansion device) by one or two performance parameters, the variation in magnitude of which is indicative of the health of that component. A hybrid inverse model is set up based on the theoretical standard refrigeration cycle in conjunction with statistically identified component models that correct for non-standard behavior of the characteristic parameters of the particular chiller. Such an approach has the advantage of using few physically meaningful parameters (as against using the numerous sensor data directly), which simplifies the detection phase while directly providing the needed diagnostic ability. Another advantage to this generic approach is that the identification of the correction models is simple and robust, since it requires regression rather than calibration. The entire methodology has been illustrated with actual monitored data from two centrifugal chillers (one a laboratory chiller and the other a field operated chiller). The sensitivity of this approach to sensor noise has also been investigated.

Original languageEnglish (US)
Pages (from-to)258-265
Number of pages8
JournalJournal of Solar Energy Engineering, Transactions of the ASME
Volume125
Issue number3
DOIs
StatePublished - Aug 2003
Externally publishedYes

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Fault detection
Refrigeration
Sensors
Condensers (liquefiers)
Evaporators
Systems engineering
Air conditioning
Failure analysis
Heat exchangers
Compressors
Identification (control systems)
Classifiers
Health
Calibration
Heating

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Fuel Technology
  • Mechanical Engineering
  • Renewable Energy, Sustainability and the Environment

Cite this

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abstract = "Model-based fault detection and diagnosis approaches based on statistical models for fault-free performance concurrently require a fault classifier database for diagnosis. On the other hand, a model with physical parameters would directly provide such diagnostic ability. In this paper, we propose a generic model development approach, called the characteristic parameter approach, which is suitable for large engineering systems that usually come equipped with numerous sensors. Such an approach is applied to large centrifugal chillers, which are generally the single most expensive piece of equipment in heating, ventilating, air-conditioning, and refrigeration systems. The basis of the characteristic parameter approach is to quantify the performance of each and every primary component of the chiller (the electrical motor, the compressor, the condenser heat exchanger, the evaporator heat exchanger, and the expansion device) by one or two performance parameters, the variation in magnitude of which is indicative of the health of that component. A hybrid inverse model is set up based on the theoretical standard refrigeration cycle in conjunction with statistically identified component models that correct for non-standard behavior of the characteristic parameters of the particular chiller. Such an approach has the advantage of using few physically meaningful parameters (as against using the numerous sensor data directly), which simplifies the detection phase while directly providing the needed diagnostic ability. Another advantage to this generic approach is that the identification of the correction models is simple and robust, since it requires regression rather than calibration. The entire methodology has been illustrated with actual monitored data from two centrifugal chillers (one a laboratory chiller and the other a field operated chiller). The sensitivity of this approach to sensor noise has also been investigated.",
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