A Hybrid Diagnosis Method for Inverter Open-circuit Faults in PMSM Drives

Zeliang Zhang, Guangzhao Luo, Zhengbin Zhang, Xuecheng Tao

科研成果: 期刊稿件文章同行评审

36 引用 (Scopus)

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
页(从-至)180-189
页数10
期刊CES Transactions on Electrical Machines and Systems
4
3
DOI
出版状态已出版 - 2020

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