Fault Diagnosis of Induction Motors Using a Recursive Kalman Filtering Algorithm
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This study describes an adaptive order-tracking fault diagnosis method using recursive Kalman ﬁltering algorithm. In this paper, a high-resolution order tracking technique based on adaptive Kalman ﬁlter is proposed for detecting the fault in an induction motor bearing. The order tracking problem has been treated as the tracking of frequency-varying bandpass signals. The algorithm is implemented on the real digital signal obtained from the vibration of induction motor to evaluate the efficiency of the proposed method. Ordered amplitudes are estimated with high-accuracy when experimental implementation is done. The results of the experiments indicate that the proposed methodology has been validated for several cases in fault diagnosis of an induction motor
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