An Experimental Study on Fault Detection and Diagnosis Method for a Water Chiller Using Bayes Classifier

베이즈 분류기를 이용한 수냉식 냉동기의 고장 진단 방법에 관한 실험적 연구

  • 이흥주 (한국과학기술연구원) ;
  • 장영수 (국민대학교 기계공학과 대학원) ;
  • 강병하 (국민대학교 기계.자동차 공학부)
  • Published : 2008.06.25

Abstract

Fault detection and diagnosis(FDD) system is beneficial in equipment management by providing the operator with tools which can help find out a failure of the system. An experimental study has been performed on fault detection and diagnosis method for a water chiller. Bayes classifier, which is one of classical pattern classifiers, is adopted in deciding whether fault occurred or not. FDD algorithm can detect refrigerant leak failure, when 20% amount of charged refrigerant for normal operation leaks from the water chiller. The refrigerant leak failure caused COP reduction by 6.7% compared with normal operation performance. When two kinds of faults, such as a decrease in the mass flow rate of cooling water and temperature sensor fault of cooling water inlet, are detected, COP is a little decreased by these faults.

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