Fault Diagnosis Method of Power Electronic Equipment Based on Improved Resnet Neural Network-Reference-Cited by-同舟云学术

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Fault Diagnosis Method of Power Electronic Equipment Based on Improved Resnet Neural Network

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 4th International Conference on Electrical Engineering and Control Technologies (CEECT)
language:
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Author:

Zhou Kai¹,Dai Ruicheng¹,Li Xue¹,Zhao Bi¹,Chen Ze¹,Guo Wenliang¹,Gao Jianjian¹

Affiliation:

1. State Grid Beijing Maintenance Company,Beijing,China,100073

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10030083/10030092/10030242.pdf?arnumber=10030242

Reference17 articles.

1. Multiple Open-Circuit Fault Diagnosis Based on Multistate Data Processing and Subsection Fluctuation Analysis for Photovoltaic Inverter

2. Fault Diagnosis and Reconfiguration for Multilevel Inverter Drive Using AI-Based Techniques

3. A Novel HVDC Double-Terminal Non-Synchronous Fault Location Method Based on Convolutional Neural Network

4. Real-Time Fault Detection and Identification for MMC Using 1-D Convolutional Neural Networks

5. Distributed sea clutter denoising algorithm based on variational mode decompositon[J];sun;Instrumentation,2020

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Network Fault Lightweight Prediction Algorithm Based on Continuous Knowledge Distillation;Lecture Notes in Electrical Engineering;2024

2. Fault Prediction of IoT Terminals based on Improved ResNet and BiLSTM Models;2023 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB);2023-06-14

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