基于深度學習的用電網絡絕緣子識別定位技術
打開文本圖片集
中圖分類號：TP319 文獻標志碼：A 文章編號：2095-2945（2025）20-0007-05
Abstract：Atpresent，mostoftheidentificationandpositioningofpower lineinsulatorsrelyonmanualwork，whichiscostly andineficient.Thedevelopmentofdeplearningtheoryhasgreatlypromotedtheintellgentidentificationandpositioningof insulators.Thispaper takes theimagerecognitionofinsulatorsinpowersupplynetworksastheresearchobject.Basedonthe deeplearningmethodandcombinedwiththeapplicationcharacteristicsofthepowersupplysafetydetectionandmonitoring devicesystem，theaplicationinintellgentrecognitionofpowersupplysafetydetectionandmoniringimagesisstudiedInthis paper，twoconvolutionalnetworksarecombined.Thenewalgorithmreduces thegenerationofredundantwindowsandusesa moreintellgentslidingmechanismtoimprovepositioningaccuracyThisimprovementmakestheunmannedmonitoringprocesof insulatorsmoreeficient，andtoacertainextentprovidestechnicalsupprtforunmannedreal-timemonitoringof powernetworks.
Keywords： electricity network;contact line; insulator; deep learning;positioning and identification
一般輸電線路或鐵路接觸網中極為重要的組件—一絕緣子，扮演著機械支撐和電氣隔離的雙重角色。（剩余5478字）