Diagnosis of Induction Motor Rotor Fault through Discrete Wavelet Transform Applied to Residual Current

Induction motors are critical components in industrial processes since their failure usually lead to an unexpected interruption at the industrial plant. The condition monitoring of the induction motors have been a challenging topic for many electrical machine researchers. Indeed, the effectiveness of the fault diagnosis and prognosis techniques depends very much on the quality of the fault features selection. However, in inductionmotor drives, rotor defects are the most complex in terms of detection since they interact with the supply frequency within a restricted band around this frequency, especially in the no-loaded case. To overcome this drawback, this paper deals with an efficient and new method to diagnose the induction-motor rotor fault based on the application of the Discrete Wavelet Transform (DWT) to the residual current, obtained by subtraction between stator current and its Time Synchronous Averaging (TSA). Simulation and experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the hybrid DWT-TSA approach. Key-Words: Condition monitoring, Diagnosis, Discrete Wavelet Transform (DWT), Induction motor, Motor Current Signature Analysis (MCSA), Rotor fault, Time Synchronous Averaging (TSA)