Improved ZSVC‐based fault detection technique for incipient stage inter‐turn fault in PMSM. Issue 12 (1st October 2019)

• Record Type: Journal Article
• Authors: Fang, Jie; Sun, Yining; Wang, Yibing; Wei, Baolei; Hang, Jun
• Is Part Of: IET electric power applications. Volume 13:Issue 12(2019)
• Page Start: 2015
• Page End: 2026
• Publication Date: 2019-10-01
• Subjects: stators -- fault diagnosis -- fast Fourier transforms -- harmonic analysis -- synchronous machines -- discrete wavelet transforms -- permanent magnet machines -- machine theory; fault diagnosis method -- PMSM -- permanent‐magnet synchronous machine -- zero‐sequence voltage component‐based inter‐turn fault detection method -- ZSVC‐based fault detection technique -- discrete wavelet transform -- harmonic components -- fast Fourier transform -- stator current; Electric power -- Periodicals; Electric power systems -- Periodicals; 621.305
• DOI: 10.1049/iet-epa.2019.0016
• Languages: English
• ISSNs: 1751-8660

Abstract

Abstract : 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.