Fault Diagnosis Based on Attention Collaborative LSTM Networks for NPC Three-Level Inverters-Reference-Cited by-同舟云学术

Fault Diagnosis Based on Attention Collaborative LSTM Networks for NPC Three-Level Inverters

Published:2022 Issue: Volume:71 Page:1-16
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Si Yupeng¹^ORCID,Wang Rongjie²^ORCID,Zhang Shiqi¹^ORCID,Zhou Wenting¹^ORCID,Lin Anhui¹^ORCID,Wang Yichun¹^ORCID

Affiliation:

1. College of Marine Engineering, Jimei University, Xiamen, China

2. Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering and the College of Marine Engineering, Jimei University, Xiamen, China

Funder

National Natural Science Foundation of China

High-Level Talent Training Project in the Transportation Industry

National Natural Science Foundation of Fujian Province

Fujian Province Office of Science and Technology Support for Army

Scientific Research Foundation of the Key Laboratory of Fishery Equipment and Engineering at Ministry of Agriculture of the People’s Republic of China

Scientific Research Foundation of the Artificial Intelligence Key Laboratory of Sichuan Province

Scientific Research Foundation of the Jiangsu Key Laboratory of Power Transmission and Distribution Equipment Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09761886.pdf?arnumber=9761886

Reference39 articles.

1. Intelligent fault diagnosis among different rotating machines using novel stacked transfer auto-encoder optimized by PSO

2. An evolving neuro-fuzzy classifier for fault diagnosis of gear systems

3. Parallel Open-Circuit Fault Diagnosis Method of a Cascaded Full-Bridge NPC Inverter With Model Predictive Control

4. Review of intelligent fault diagnosis methods for three-phase voltage-mode inverters;ma;Zhongguo Dianji Gongcheng Xuebao,2020

5. Review of intelligent fault diagnosis methods for three-phase voltage-mode inverters;ma;Zhongguo Dianji Gongcheng Xuebao,2020

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