Open AccessImproved ZSVC‐based fault detection technique for incipient stage inter‐turn fault in PMSM
Author(s) -
Fang Jie,
Sun Yining,
Wang Yibing,
Wei Baolei,
Hang Jun
Publication year - 2019
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
ISSN - 1751-8679
DOI - 10.1049/iet-epa.2019.0016
Subject(s) - fault detection and isolation , fault (geology) , stator , fault indicator , control theory (sociology) , wavelet , stuck at fault , computer science , noise (video) , signal (programming language) , harmonic , engineering , electronic engineering , artificial intelligence , acoustics , electrical engineering , actuator , physics , control (management) , seismology , geology , image (mathematics) , programming language
Fault detection plays an important role in providing reliable operation for permanent‐magnet synchronous machine (PMSM). The inter‐turn fault is one of the most common faults for the PMSM. Hence, this study focuses on the incipient stage inter‐turn fault detection. An improved zero‐sequence voltage component‐based (ZSVC) inter‐turn fault detection method is proposed. In the proposed method, discrete wavelet transform is first applied to remove the noise and harmonic components in the ZSVC for highlighting the fault characteristic component. Then, fast Fourier transform is used to analyse the obtained signal for the inter‐turn fault detection. In addition, to show the performance of the proposed method, the commonly used fault detection based on stator current is studied. The effectiveness of the proposed fault diagnosis method is validated by the simulation and experimental results, showing that the proposed method has good performance for the incipient stage inter‐turn fault diagnosis.