Turn-to-turn and phase-to-phase short circuit fault detection of wind turbine permanent magnet generator based on equivalent magnetic network modelling by wavelet transform approach

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-05-30 DOI:10.1049/elp2.12452

Mehrage Ghods, Zabihollah Tabarniarami, Jawad Faiz, Mohammad Amin Bazrafshan

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引用次数: 0

Abstract

One of the most common faults in electric machines is a turn-to-turn short circuit (TTSC), which may destroy coil insulation and demagnetise the magnet. In addition, the phase-to-phase short circuit (PPSC) fault, which can have even more destructive effects than the TTSC fault, is introduced and analysed. The equivalent magnetic network (EMN) method, with high modelling accuracy and a short computation time, is employed for healthy and faulty machines. The current signal under fault conditions is analysed in the dqo frame, showing the presence of the second harmonic component in its waveform. This fault detection index is processed using the signal processing technique of discrete(wavelet transform (DWT). Besides, energy analysis is used to distinguish TTSC and PPSC faults. Finally, finite element and EMN modelling results are compared with the experimental data of the prototyped permanent magnet generator. The results show that the combination of the proposed EMN method and DWT has very good accuracy and speed. Furthermore, the proposed fault detection method remains unaffected by various linear loads with different power factors.

The cover image is based on the article Turn-to-turn and phase-to-phase short circuit fault detection of wind turbine permanent magnet generator based on equivalent magnetic network modelling by wavelet transform approach by Mehrage Ghods et al., https://doi.org/10.1049/elp2.12452

Abstract Image

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基于小波变换方法等效磁网络建模的风力涡轮永磁发电机匝间和相间短路故障检测

电机最常见的故障之一是匝间短路 (TTSC)，它可能会破坏线圈绝缘并使磁铁退磁。此外，还介绍并分析了相间短路 (PPSC) 故障，这种故障比 TTSC 故障的破坏性更大。等效磁网络 (EMN) 方法具有建模精度高、计算时间短的特点，适用于健康和故障机器。在 dqo 框架下分析了故障条件下的电流信号，显示其波形中存在二次谐波分量。该故障检测指标采用离散（小波变换）信号处理技术进行处理。此外，还利用能量分析来区分 TTSC 和 PPSC 故障。最后，将有限元和 EMN 建模结果与原型永磁发电机的实验数据进行了比较。结果表明，建议的 EMN 方法与 DWT 的结合具有很好的准确性和速度。此外，提出的故障检测方法不受不同功率因数的各种线性负载的影响。封面图片来自 Mehrage Ghods 等人撰写的文章《基于小波变换方法的等效磁网络建模的风力涡轮永磁发电机匝间和相间短路故障检测》，https://doi.org/10.1049/elp2.12452。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.