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Incipient Interturn Short-Circuit Fault Diagnosis of Permanent Magnet Synchronous Motors Based on the Data-Driven Digital Twin Model by Zhichao Chen; Deliang Liang; Shaofeng Jia; Lin Yang; Shuzhou Yang is a Engineering article available to read on EtoBox.

What is Incipient Interturn Short-Circuit Fault Diagnosis of Permanent Magnet Synchronous Motors Based on the Data-Driven Digital Twin Model about?

As the most common fault of permanent magnet synchronous motor, inter-turn short circuit fault has great harm and develops rapidly. Once it is not diagnosed in time, it will bring secondary damage to the motor system. In the process of early fault diagnosis, the harmonic of the motor often increases the difficulty of fault feature extraction. In order to improve the reliability of the system, a method for early inter-turn short circuit diagnosis of permanent magnet synchronous motors based on data-driven digital twin models is proposed in this paper. Firstly, the three-phase current residuals of the permanent magnet synchronous motor under inter-turn short circuit fault are analyzed theoretically. Secondly, the digital twin model of the target motor in healthy states is established through NARX(Nonlinear Auto-Regressive model with Exogenous Inputs) network. Finally, the early short circuit diagnosis is completed through the analysis of the three-phase current residual. The method proposed in this paper does not need fault data and can complete the diagnosis of minor faults under the condition of large harmonic and certain inherent asymmetry. It has high sensitivity and obvious faul

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Author

Zhichao Chen; Deliang Liang; Shaofeng Jia; Lin Yang; Shuzhou Yang

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Published

2023

Language

EN

Field

Engineering (Physical Sciences)