Automatic Demagnetization Fault Location of Direct-Drive Permanent Magnet Synchronous Motor Using Knowledge Graph

Demagnetization fault in a direct-drive permanent magnet synchronous motor (DDPMSM) degrades its energy efficiency and performance, and even causes unscheduled downtime. To shorten the fault recovery time of demagnetization fault, reduce motor maintenance costs, and develop a fault-tolerant strategy, it is necessary to study early and automatic fault detection and location technology. However, the current fault location methods either fail to locate arbitrary demagnetization faults or require a large number of search coils. These methods have not yet studied the automatic location of faults. In this article, a method based on knowledge graph (KG) is proposed to automatically locate demagnetization faults in arbitrary demagnetization conditions. First, three toroidal-yoke-type search coils are installed on stator slots, and three fault location signals (FLSs) are constructed based on the back electromotive force of search coils. The FLSs under different demagnetization fault types are investigated. Second, two fault indicators are extracted from the FLSs and used as input to the KG. The correspondence between fault indicators and demagnetization fault types is established. Simulation results show that the proposed indicators have good robustness to the operating conditions and motor design. Third, a KG system is established according to the constructed relationship. The system is tested by a database derived from experiments and finite element models. Test results demonstrate that the proposed method can automatically locate demagnetization fault with a minimum detectable severity of 10% for each faulty permanent magnet. Finally, experiments are conducted to verify the correctness and effectiveness of the proposed method.