Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/9830
Title: Fuzzy-genetic algorithm for automatic fault detection in HVAC systems
Authors: Lo, CH
Chan, PT
Wong, YK
Rad, AB
Cheung, KL
Keywords: Air-conditioning systems
Fault detection
Fuzzy logic
Genetic algorithms
Issue Date: 2007
Publisher: Elsevier
Source: Applied soft computing, 2007, v. 7, no. 2, p. 554-560 How to cite?
Journal: Applied soft computing 
Abstract: 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.
URI: http://hdl.handle.net/10397/9830
ISSN: 1568-4946
EISSN: 1872-9681
DOI: 10.1016/j.asoc.2006.06.003
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

39
Last Week
0
Last month
0
Citations as of Jul 28, 2017

WEB OF SCIENCETM
Citations

32
Last Week
0
Last month
0
Citations as of Jul 27, 2017

Page view(s)

43
Last Week
2
Last month
Checked on Jul 9, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.