A model-based fault detection and diagnosis strategy for HVAC systems

Qiang Zhou, Shengwei Wang, Zhenjun Ma

Research output: Journal article publicationJournal articleAcademic researchpeer-review

53 Citations (Scopus)

Abstract

A strategy of fault detection and diagnosis (FDD) for HVAC sub-systems at the system level is presented in this paper. In the strategy, performance indices (PIs) are proposed to indicate the health condition of different sub-systems including cooling tower system, chiller system, secondary pump systems before heat exchangers, heat exchanger system and secondary pump system after heat exchangers. The regression models are used to estimate the PIs as benchmarks for comparison with monitored PIs. The online adaptive threshold determined by training data and monitored data is used to determine whether the PI residuals between the estimation and calculation or monitoring are in the normal working range. A dynamic simulation platform is used to simulate the faults of different sub-systems and generate data for training and validation. The proposed FDD strategy is validated using the simulation data and proven to be effective in the FDD of heating, ventilating and air-conditioning (HVAC) sub-systems.
Original languageEnglish
Pages (from-to)903-918
Number of pages16
JournalInternational Journal of Energy Research
Volume33
Issue number10
DOIs
Publication statusPublished - 6 Oct 2009

Keywords

  • Fault detection
  • Fault diagnosis
  • HVAC system
  • Model-based

ASJC Scopus subject areas

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

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