DocumentCode :
504576
Title :
Automated fault diagnosis method for a variable air volume air handling unit
Author :
Han, Dong-Won ; Chang, Young-Soo
Author_Institution :
Korea Inst. of Sci. & Technol., Seoul, South Korea
fYear :
2009
fDate :
18-21 Aug. 2009
Firstpage :
2012
Lastpage :
2017
Abstract :
Automated control methods in building HVAC systems have been widely applied. It is known that poorly maintained, degraded, and improperly controlled equipment wastes 15% to 30% of energy used in commercial buildings. So, we need to detect and cope with abnormal event of target system using intelligent control system. The expert rules were developed for application to single-duct variable air volume or constant air volume air handling unit. Expert rules are composed of 28 rules using only a small number of temperatures and control signals. If any one of rules is satisfied, a fault is indicated. In this study, we tested the performance of FDD method by expert rule using simulation data under single fault and multiple faults cases. Test of the expert rule set was performed using no-fault and faulty data produced by a simulation of a three-zone building conditioned with a VAV AHU. The simulations were carried out using summer season weather data in Seoul during the occupied period under no-fault and faulty conditions. FDD method using expert rules was found to indicate each fault accurately under single fault and multiple faults.
Keywords :
HVAC; building management systems; expert systems; fault diagnosis; intelligent control; FDD method; VAV AHU; abnormal event detection; automated fault diagnosis method; building HVAC system; expert rule; intelligent control system; single-duct variable air volume air handling unit; target system; Automatic control; Control systems; Degradation; Ducts; Event detection; Fault diagnosis; Intelligent control; Temperature control; Testing; User-generated content; Automated fault diagnosis method; Expert rules; FDD; HVAC system; VAV AHU;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
ICCAS-SICE, 2009
Conference_Location :
Fukuoka
Print_ISBN :
978-4-907764-34-0
Electronic_ISBN :
978-4-907764-33-3
Type :
conf
Filename :
5334194
Link To Document :
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