Time-Frequency Domain Lightweight Dual-Branch MSCFormer for PMSM ITSC Fault Diagnosis

This article presents a novel method for diagnosing interturn short circuits (ITSC) in permanent magnet synchronous motors (PMSMs) utilizing a transformer-based hybrid architecture. The influence of ITSC on dq-axis currents at different fault severity levels is first analyzed mathematically, providing a foundation for extracting distinctive spectral features. Building on this analysis, a motor short-circuit transformer (MSCFormer) is proposed, employing a dual-branch framework to effectively integrate and exploit faulty features from both the time and frequency domains. This dual-domain approach enhances diagnostic accuracy and robustness by utilizing the complementary perspective provided by frequency-domain spectral features, such as the 2nd, 4th and other harmonics. Additionally, the network incorporates an adaptive feature-level fusion strategy, lightweight optimization, and the multihead attention mechanism to mitigate noise interference and improve generalization. Comprehensive experimental evaluations demonstrate the effectiveness and superiority of the proposed method in terms of accuracy and network complexity, achieving 99.79% overall accuracy (OA) and 99.79% F1-score, with only 0.156 million parameters and 1.77 million floating point operations (FLOPs). Code is available at https://github.com/uoe-haoyu/PMSM_Fault_Diagnosis_DL.