Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 1997.07b
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- Pages.485-487
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- 1997
Fault Diagnosis for a Variable Air Volume Air Handling Unit
공조 시스템에서의 자동 이상 검출 및 진단 기술
- Lee, Won-Yong (KIER) ;
- Shin, Dong-Ryul (KIER) ;
- Park, Cheol (National Institute of Standards and Technology USA.)
- Published : 1997.07.21
Abstract
Schemes for detecting and diagnosing faults are presented. Faults are detected when residuals change significantly and thresholds are exceed. Two stage artificial neural networks are applied to diagnose faults. The idealized steady state patterns of residuals are defined and learned by ANNs using back propagation algorithm. The first stage ANN is trained to classify the subsystem in which the various faults are located. The first stage ANN could be also used to detect faults with threshold, checking. The second stage ANNs are trained to discriminate the specific cause of a fault at the subsystem level.
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