Non-stationary in Electric Motor
Non-stationary in Electric Motor
The variable-speed PMSM drive system may cause variation of the fault characteristic frequency, and the fault should then be diagnosed in the non-stationary state. For feature extraction from non-stationary signals, time–frequency analysis methods, such as short-time Fourier transform (STFT) and wavelet transform, are very popular. In [18], fault detection in power transformers was studied; both STFT and wavelet transform were used to process the neutral and/or capacitively transformed currents recorded during an impulse test. In [19–22], wavelet transform was applied to analyze the signals in the electrical motor under a non-stationary condition. When applying STFT, a suitable window size is needed to match with the specific frequency content of the signal, which is generally not known in advance [20]. This leads to an inconsistent treatment of different current frequencies because of the fixed length of the window. Hence, it is not suitable for fault detection when the motor is not operating at constant speed. Wavelet transform solves the non-stationary problem by decomposing a time series into time/frequency space simultaneously. It can provide a good resolution in time for high-frequency components of a signal and a good resolution in frequency for low frequency components. In this sense, wavelets have a window that is automatically adjusted to give the appropriate resolution developed by its approximation and detail signals, thus making it a very suitable approach to detect the faults of electrical machine in a non-stationary state. Non-stationary State In this section, the reference rotor speed of the PMSM is variable and shown in Figure 7, where the speed is linear decreased from 1000r/min at 0.5 sec to 700 r/min at 2.5 sec.
(zhangDiagnosisMechanicalUnbalance2016, link, DOI, zolib) said: