"Three-phase PMSM with ITSC faults of stator winding Dataset"

"Permanent magnet synchronous motors (PMSMs) are critical components for electromechanical energy conversion in renewable energy systems and electrified transportation. However, inter turn short-circuit (ITSC) faults in stator windings account for over 33% of motor failures, severely threatening system reliability and economic operation. High-performance artificial intelligence-based fault diagnosis methods rely on high-quality datasets that encompass diverse operating conditions and fault severity levels\u2014a critical feature that is generally lacking in existing open-source data. To address this gap, this study presents and releases a novel dataset of inter-turn short-circuit faults in PMSMs. The dataset was collected from a custom-designed fault prototype, covering 12 torque-speed operating conditions, 9 levels of shorted turn percentages, and 3 short-circuit resistance values. It synchronously records three-phase voltage, three-phase current, and short-circuit current signals, thereby effectively simulating the gradual degradation process of stator winding insulation systems. Benchmark evaluations using a CNN-1D model systematically assess the performance of AI methods in terms of diagnostic accuracy and cross-operating condition transferability. The results demonstrate that this dataset effectively facilitates the training of AI models and yields reliable diagnostic outcomes, validating its value as a high-quality dataset. Furthermore, the dataset is promising for applications such as fault modeling validation, incipient fault diagnosis, transfer learning task design, and fault severity estimation, thereby filling a critical data gap in the power and energy domain."