高电压技术2024，Vol.50Issue(5)：1889-1899,中插8,12.DOI:10.13336/j.1003-6520.hve.20230578
基于多尺度特征融合的绝缘子缺陷程度检测
Insulator Defect Degree Detection Based on Multi-scale Feature Fusion
摘要
Abstract
Insulator defects with different degrees have similar features and less pixel information,resulting in poor de-tection effect,therefore,an insulator defect degree detection network based on multi-scale feature fusion(MFFD3Net)is proposed.The network uses reconstructed ResNeSt50 to improve the feature extraction ability in insulator defect dataset.A multi-scale feature fusion module based on deconvolution is designed,which enriches the expression ability of different size feature maps and improves the detection performance of different scale targets.At the same time,the receptive field block(RFB)is added after the shallow feature maps of the input detection module to ensure more insulator defect infor-mation to enter the effective receptive field,which has an impact on the final feature map and improves the detection accuracy of insulator defects in different degrees.The mAP of MFFD3Net on insulator defect degree dataset reaches 85.02%,the detection accuracy of small targets such as slight breakage and slight flashover is 78.37%and 79.98%,which can complete the identification and location of insulator defects in different degrees.Thus,the MFFD3Net proposed in this paper is of great significance for improving the fault warning of power system and ensuring the safe and stable operation of power grid.关键词
绝缘子/缺陷程度检测/ResNeSt50/特征提取模块/感受野Key words
insulator/defect degree detection/ResNeSt50/RFB/receptive field引用本文复制引用
陈奎,贾立娇,刘晓,方永丽,赵昌新..基于多尺度特征融合的绝缘子缺陷程度检测[J].高电压技术,2024,50(5):1889-1899,中插8,12.基金项目
江苏省研究生科研与实践创新计划(SJCX23_1324) （SJCX23_1324）
中国矿业大学研究生创新计划(2023WLJCRCZL351) （2023WLJCRCZL351）
国网江苏省电力有限公司科技项目(J2021044).Project supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province(SJCX23_1324),Graduate Innovation Program of China University of Mining and Technology(2023WLJCRCZL351),Science and Technology Program of State Grid Jiangsu Electric Power Corporation Limited(J2021044). （J2021044）
