基于人工智能的电力电子变换器开路故障诊断研究综述

Translated title of the contribution: Review for AI-based Open-circuit Faults Diagnosis Methods in Power Electronics Converters

Chuang Liu*, Lei Kou, Guowei Cai, Zihan Zhao, Zhe Zhang

*Corresponding author for this work

Research output: Contribution to journalReviewResearchpeer-review

Abstract

Power electronics converters have been widely used in aerospace system, DC transmission, distributed energy, smart grid and so forth, and their reliability has been a hot spot in academia and industry. It is of great significance to carry out power electronics converters open-circuit faults monitoring and intelligent fault diagnosis to avoid secondary faults, reduce time and cost of operation and maintenance, and improve the reliability of power electronics system. Firstly, the faults features of power electronic converters are analyzed and summarized. Secondly, some AI-based fault diagnosis methods and application examples with power electronics converters are reviewed, and a fault diagnosis method based on the combination of random forests and transient fault features is proposed for the three-phase power electronics converters. Finally, the future research challenges and directions of AI-based fault diagnosis methods are pointed out.

Translated title of the contributionReview for AI-based Open-circuit Faults Diagnosis Methods in Power Electronics Converters
Original languageChinese
JournalDianwang Jishu/Power System Technology
Volume44
Issue number8
Pages (from-to)2957-2970
ISSN1000-3673
DOIs
Publication statusPublished - 5 Aug 2020

Keywords

  • Artificial intelligence (AI)
  • Data-driven
  • Faults diagnosis
  • Faults location
  • Open-circuit faults
  • Power electronics converters

Fingerprint Dive into the research topics of 'Review for AI-based Open-circuit Faults Diagnosis Methods in Power Electronics Converters'. Together they form a unique fingerprint.

Cite this