Fuzzy-genetic algorithm for automatic fault detection in HVAC systems

C. H. Lo, P. T. Chan, Y. K. Wong, A. B. Rad, K. L. Cheung

Research output: Contribution to journalArticlepeer-review

60 Citations (Scopus)


Detecting fault before it deteriorates the system performance is crucial for the reliability and safety of many engineering systems. This paper develops an intelligent technique based on fuzzy-genetic algorithm (FGA) for automatically detecting faults on HVAC system. Many researchers have proposed only using fuzzy systems to effect fault detection and diagnosis. Other applications of the FGA are mainly focused on the synthesis of fuzzy control rules. The proposed automatic fault detection system (AFD) monitors the HVAC system states continuously by fuzzy system. The optimization capability of genetic algorithms allows the generation of optimal fuzzy rules. Faults are represented as different fault levels in the AFD system and are distinguished by fuzzy system after tuning its rule table. Simulation studies are conducted to verify the proposed AFD system for the single zone air handler system.

Original languageEnglish
Pages (from-to)554-560
Number of pages7
JournalApplied Soft Computing Journal
Issue number2
Publication statusPublished - Mar 2007


  • Air-conditioning systems
  • Fault detection
  • Fuzzy logic
  • Genetic algorithms


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