| Title |
An Experimental Study on Fault Detection and Diagnosis Method for a Water Chiller Using Bayes Classifier |
| Authors |
이흥주(Heungju Lee) ; 장영수(Young-Soo Chang) ; 강병하(Byung Ha Kang) |
| Keywords |
고장검출 및 진단 ; 수냉식 냉동기 ; 베이즈 분류기 Fault detection and diagnosis ; Water chiller ; Bayes classifier |
| 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. Failure modes in this study include refrigerant leakage, decrease in mass flow rate of the chilled water and cooling water, and sensor error of the cooling water inlet temperature. It is possible to detect and diagnose faults in this study by adopting FDD algorithm using only four parameters(compressor outlet temperature, chilled water inlet temperature, cooling water outlet temperature and compressor power consumption). Refrigerant leakage failure is detected at 20% of refrigerant leakage. When mass flow rate of the chilled and cooling water decrease more than 8% or 12%, FDD algorithm can detect the faults. The deviation of temperature sensor over 0.6℃ can be detected as fault. |