Current Signature Analysis for Condition Monitoring of Motors

This paper presents a novel approach to current signature analysis based on wavelet transform of the stator current. The proposed method lies in the fact that by using wavelet transform, the inherent non-stationary nature of stator current can be accurately considered. The key characteristics of the proposed method are its ability to provide feature representations of multiple frequency resolutions for faulty modes, ability to clearly differentiate between healthy and faulty conditions, and its applicability to non-stationary signals. Successful implementation of the system for different types of motors is demonstrated in the paper. Another technique Current Park’s Vector is also discussed in this paper. The Park’s Vector approach can be used to detect the different types of motor’s faults. An undamaged machine shows a perfect circle in Park’s Vector representation whereas an unbalance due to winding faults results in an elliptic representation of the Park’s vector. Thus, faulty motor can be easily detected by comparing both patterns. The park’s vector pattern for different types of faults of motor is analyzed in the paper. Keywords-Condition Monitoring, Fault Diagnosis, Electrical Machines, MCSA