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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Modular multilevel converters (MMCs) have a complex structure and a large number of submodules (SMs). If there is a fault in one of the SMs, it will affect the reliable operation of the system. Therefore, rapid fault diagnosis and accurate fault positioning are crucial to ensuring the continuous operation of the system. However, the IGBT open-circuit faults in different submodules of MMCs have similar fault features, and the traditional fault feature extraction method cannot effectively extract the key features of the fault so as to accurately locate the faulty submodules. In response to this problem, this paper proposes a fault diagnosis method based on weighted-amplitude permutation entropy (WAPE) and DS evidence fusion theory. The simulation results show that WAPE has better feature extraction ability than basic permutation entropy, and the fused multiscale feature decision output has better diagnostic accuracy than the single-scale feature. Compared with traditional fault diagnosis methods, this method achieves the diagnosis of multiple fault types by collecting a single signal, which greatly reduces the number of samples and leads to higher diagnostic accuracy and faster diagnostic speed.

Details

Title
IGBT Open-Circuit Fault Diagnosis for MMC Submodules Based on Weighted-Amplitude Permutation Entropy and DS Evidence Fusion Theory
Author
Shen, Yifei 1   VIAFID ORCID Logo  ; Wang, Tianzhen 1   VIAFID ORCID Logo  ; Amirat, Yassine 2   VIAFID ORCID Logo  ; Chen, Guodong 3 

 College of Logistics Engineering, Shanghai Maritime University, Shanghai 201306, China; [email protected] 
 L@bISEN, ISEN Yncréa Ouest, Brest Campus, 20, Rue Cuirassé Bretagne, 29200 Brest, France 
 Shanghai Electric Power Transmission & Distribution Group Shanghai Electric Group Co., Ltd., Shanghai 200042, China; [email protected] 
First page
317
Publication year
2021
Publication date
2021
Publisher
MDPI AG
e-ISSN
20751702
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2612793584
Copyright
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.