基于深度學(xué)習(xí)的用電網(wǎng)絡(luò)絕緣子識別定位技術(shù)

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中圖分類號：TP319 文獻(xiàn)標(biāo)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(wǎng)中極為重要的組件—一絕緣子，扮演著機(jī)械支撐和電氣隔離的雙重角色。（剩余5478字）