Fault detection and diagnosis using Principal Component Analysis of vibration data from a reciprocating compressor

M Ahmed, M Baqqar, F Gu, A D Ball
2012 Proceedings of 2012 UKACC International Conference on Control  
This paper investigates the use of time domain vibration features for detection and diagnosis of different faults from a multi stage reciprocating compressor. Principal Component Analysis (PCA) is used to develop a detection and diagnosis framework in that the effective diagnostic features are selected from PCA of 14 potential features and a PCA model based detection method using ' and statistics is subsequently developed to detect various faults including suction valve leakage, inter-cooler
more » ... ge, inter-cooler leakage, loose drive belt, and combinations of discharge valve leakage with suction valve leakage, suction valve leakage with intercooler leakage and discharge valve leakage with intercooler leakage. A study of -contributions has found two original features: Histogram Lower Bound and Normal Negative loglikelihood which allow full classification of different simulated faults.
doi:10.1109/control.2012.6334674 fatcat:r62pbxyjqrg4zbj4gjbgcw42uq