Methods to identify intermittent electrical and mechanical faults in permanent magnet AC drives based on time-frequency analysis

Prognosis of failures of electric drives can be achieved through the detection of non-catastrophic conditions, recognized as faults. As the frequency and severity of these faults increase, the expected working life of the drive decreases, leading to eventual failure. The goal of this work is to develop new techniques which can detect and classify conditions in electric drives which lead to failure. In this work, methods are presented to identify developing electrical and mechanical faults based on both Fourier and wavelet analysis of the field oriented currents in PMAC drives. Linear discriminant analysis is used to classify between the fault types. This dissertation includes a survey of diagnostic approaches used for various machine types. The experimental setup and results from testing are included.