A New MSCSA Technique for Induction Motor Diagnosis Based on the Park Transform Approach

Induction machines play a crucial role in industrial applications, making preventive maintenance combined with fault diagnosis techniques essential for ensuring reliable operation. One of the most widely used diagnostic methods for induction machines is Motor Current Signature Analysis (MCSA). However, this technique has certain limitations, particularly in the detection of incipient or small faults. Another well-established technique is Motor Square Current Signature Analysis (MSCSA), which overcomes some of the limitations of MCSA by extracting additional fault-related information from the motor current signals. This paper proposes a new diagnostic technique, designated MSCSA-APT (Motor Square Current Signature Analysis–Alternative Park Transform), based on the spectral analysis of motor currents. Compared with the conventional MSCSA method, the proposed approach provides additional information from the frequency-domain analysis, thereby improving fault detection capability. The method is based on the square of the motor square current signal and employs an Alternative Park Transform (APT) to enhance the extraction of fault signatures. Simulation and experimental results are presented to validate the proposed approach. Although the method has been evaluated for the identification of different types of faults, it is particularly effective in detecting stator short-circuit faults.