摘要
In order to improve the evaluation process of inverter open-circuit faults diagnosis in permanent magnet synchronous motor (PMSM) drives, this paper presents a diagnosis method based on current residuals and machine learning models. The machine learning models are introduced to make a comprehensive evaluation for the current residuals obtained from a state observer, instead of evaluating the residuals by comparing with thresholds. Meanwhile, fault diagnosis and location are conducted simultaneously by the machine learning models, which simplifies the diagnosis process. Besides, a sampling strategy is designed to implement the proposed scheme online. Experiments are carried out on a DSP based PMSM drive, and the effectiveness of the proposed method is verified.
源语言 | 英语 |
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页(从-至) | 180-189 |
页数 | 10 |
期刊 | CES Transactions on Electrical Machines and Systems |
卷 | 4 |
期 | 3 |
DOI | |
出版状态 | 已出版 - 2020 |