General approaches of fault diagnosis and condition monitoring of squirrel-cage induction motor: a review

The induction motor suffers from numerous faults and these faults consequence into lowering of overall industrial productivity and increased shutdown period. Thus, there is the need of prior detection of numerous faults while in operation. The condition monitoring and faults diagnosis mechanism are required to formulate a well-defined and skilled map in between motor signals as well as indications of the fault state of the induction motor. Hence, a number of advanced and optimum approaches have been identified, and employed for detecting various faults in a squirrel-cage induction motor. Faults in the motor pose their signature frequencies as harmonics in the motor current spectrum. In Motor Current Signature Analysis, various approaches like Park’s vector scheme, Fast Fourier Transformation (FFT), Discrete Wavelet Transform (DWT) based digital signal processing techniques have been taken into consideration. Implementation with VLSI based diagnosis opens a broad door for its employment in numerous industrial and real-time application development.