Diagnose fault of induction motor with Wigner distribution
Jiang Jianguo, Zhang Zhiping, Qiu Arui Department of Electrical Engineering
The paper presents an approach of extracting fault feature of induction motor, which extracts the (1 -2s) f component (s-slip of motor, f-main power frequency) from the Time Frequency Spectrum (TFS) of the current of stator winding during start process. The TFS is made with Wigner-Ville Distribution. The results of applying it to induction motors in lab show that the approach has advantages of higher sensitivity and more abundant information than the traditional spectrum analysis of stable state current of stator winding, and provides a way that might identify the double cage induction motor whether with a small amount of outer cage broken bar or not.