Characteristic analysis of multi-source fault information of inter-turn short-circuit fault in rotor windings

Wang Yi; Xu Baichuan; Sun Songjun; Luo Chaoyueling; Huang Yuhao; Yang Kai

doi:10.1117/12.2640182

1 August 2022 Characteristic analysis of multi-source fault information of inter-turn short-circuit fault in rotor windings

Wang Yi, Xu Baichuan, Sun Songjun, Luo Chaoyueling, Huang Yuhao, Yang Kai

Author Affiliations +

Proceedings Volume 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022); 1225729 (2022) https://doi.org/10.1117/12.2640182
Event: 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 2022, Guangzhou, China

Abstract

The inter-turn short-circuit fault in rotor windings has a destructive impact on the wound rotor synchronous motor. It is necessary to identify the fault timely and accurately in the early stage of the fault in order to avoid serious losses. Most of the existing fault diagnosis methods are sensor detection for a single fault feature, which is difficult to ensure high diagnosis accuracy for a long time. This paper analyzes the multi-source fault characteristics of inter-turn short-circuit fault in rotor windings, and can accurately identify the fault type by relying on a variety of signals. Firstly, this paper analyzed the time domain and frequency domain characteristics of motor voltage and current performance and rotor under unbalanced magnetic tension. Then, considering the actual running state of the motor, the accurate model of the motor is established using the finite element simulation tool, and the multi-physical field coupling simulation is carried out for the fault. The multi-source fault information characteristics are analyzed from the perspectives of electromagnetism, heat and force. Compared with various information of the normal motor, the motor rotor fault can be identified quickly and accurately.

Citation Download Citation

Wang Yi, Xu Baichuan, Sun Songjun, Luo Chaoyueling, Huang Yuhao, and Yang Kai "Characteristic analysis of multi-source fault information of inter-turn short-circuit fault in rotor windings", Proc. SPIE 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 1225729 (1 August 2022); https://doi.org/10.1117/12.2640182

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KEYWORDS

Electromagnetism

Magnetism

Sensors

Teeth

Bromine

Field effect transistors

Finite element methods

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