Scale-Free and Phase-Agnostic Detection of Interturn Short-Circuit Faults in Permanent Magnet Synchronous Motors

Abstract

This study presents a scale-free and phase-agnostic method for detecting interturn short-circuit faults (ISCFs) in the stator windings of permanent magnet synchronous motors (PMSMs). The proposed method integrates denoising and feature extraction with a crest-factor-based health indicator. A wavelet-based denoising method with average peak extraction is devised to enhance the sensitivity to fault-induced current deviations while suppressing external noise. The crest factor is modified to enable phase-agnostic detection across stator windings. To eliminate scale dependency associated with motor capacity, the modified crest factor is further calibrated using baseline data obtained under healthy conditions. The resulting health indicator, namely max-min crest factor, enables consistent and reliable ISCF detection without requiring motor-specific parameters or prior knowledge of the faulty phase. The effectiveness of the proposed method is validated through multiple case studies, including 1) numerical simulations, 2) laboratory-scale testbed experiments on small-capacity PMSMs (100 W and 1 kW), and 3) full-scale testing on an 82.5 kW PMSM under realistic operating conditions. The experimental results demonstrate that the method reliably detects ISCFs regardless of fault location or motor scale.