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THz Wave Detection of Gap Defects Based on a Convolutional Neural Network Improved by a Residual Shrinkage Network

Zhonghao Zhang Guozheng Peng Yuanpeng Tan Tianjiao Pu Liming Wang

中国电机工程学会电力与能源系统学报(英文)2023，Vol.9Issue(3)：P.1078-1089,12.

中国电机工程学会电力与能源系统学报(英文)2023，Vol.9Issue(3)：P.1078-1089,12.DOI:10.17775/CSEEJPES.2020.02460

THz Wave Detection of Gap Defects Based on a Convolutional Neural Network Improved by a Residual Shrinkage Network

Zhonghao Zhang ¹Guozheng Peng ¹Yuanpeng Tan ¹Tianjiao Pu ¹Liming Wang²

作者信息

1. China Electric Power Research Institute
2. Tsinghua Shenzhen International Gradual School,Shenzhen 518055,China
折叠

摘要

关键词

Convolutional neural network/defect detection/insulation equipment/terahertz wave

分类

信息技术与安全科学

引用本文复制引用

Zhonghao Zhang,Guozheng Peng,Yuanpeng Tan,Tianjiao Pu,Liming Wang..THz Wave Detection of Gap Defects Based on a Convolutional Neural Network Improved by a Residual Shrinkage Network[J].中国电机工程学会电力与能源系统学报(英文),2023,9(3):P.1078-1089,12.

基金项目

supported by the National Key R&D Program of China:Research and application of work robot system for electric power industry(2018YFB1307400) （2018YFB1307400）

the Science and Technology Project of State Grid Corporation of China(No:SGSDDK00KJJS2000090) （No:SGSDDK00KJJS2000090）

the self-funded project of China Electric Power Research Institute:Research on detection and recognition of photovoltaic panels and health status evaluation technology based on deep learning. （）

中国电机工程学会电力与能源系统学报(英文)

OACSCDCSTPCDEI

ISSN：2096-0042

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