Fault detection and diagnosis simulation for CAV AHU system

Title
Fault detection and diagnosis simulation for CAV AHU system
Authors
한동원장영수김서영김용찬
Keywords
Fault detection and diagnosis; HVAC equipment; Normalized distance method; Classifier; 고장검출 및 진단; 공조설비; 표준화 거리 기법; 분류기
Issue Date
2010-10
Publisher
설비공학논문집
Citation
VOL 22, NO 10, 687-696
Abstract
In this study, FDD algorithm was developed using the normalized distance method and general pattern classifier method that can be applied to constant air volume air handling unit(CAV AHU) system. The simulation model using TRNSYS and EES was developed in order to obtain characteristic data of CAV AHU system under the normal and the faulty operation. Sensitivity analysis of fault detection was carried out with respect to fault progress. When differential pressure of mixed air filter increased by more than about 105 pascal, FDD algorithm was able to detect the fault. The return air temperature is very important measurement parameter controlling cooling capacity. Therefore, it is important to detect measurement error of the return air temperature. Measurement error of the return air temperature sensor can be detected at below 1.2℃ by FDD algorithm. FDD algorithm developed in this study was found to indicate each failure modes accurately.
URI
http://pubs.kist.re.kr/handle/201004/39421
ISSN
1229-6422
Appears in Collections:
KIST Publication > Article
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