Current signal analysis and processing used in fault diagnosis of permanent-magnetic DC motor

Fault features have been extracted from the armature current by several signal processing means including Fourier analysis, wavelet analysis and statistical methods after analyzing the armature current characteristics of the low power permanent-magnetic DC motor, and then the fault mechanism was analyzed. The consistency between the results of experiment and the theoretical analysis shows that the main fault features are included in the armature current described as follows: average static current i_av, standard deviation i_std, the frequency of static current f_w, the peak value i_m of starting current and the slope k of vicinal peak value point. So it is feasible to take these five parameters as characteristic parameters for fault diagnosis.