基于深度卷積神經(jīng)網(wǎng)絡(luò)的變電一次設(shè)備故障檢測(cè)方法研究

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摘要：該文介紹了一種變電一次設(shè)備故障檢測(cè)方法：通過(guò)不同光照環(huán)境收集一次設(shè)備的圖像，創(chuàng)建設(shè)備數(shù)據(jù)集并進(jìn)行預(yù)處理，通過(guò)深度卷積神經(jīng)網(wǎng)絡(luò)提取設(shè)備特征并加以檢測(cè)。經(jīng)檢測(cè)，此方法能夠明顯降低變電一次設(shè)備故障的漏報(bào)和誤報(bào)率。

關(guān)鍵詞：卷積神經(jīng)網(wǎng)絡(luò)；變電站；一次設(shè)備；故障檢測(cè)

doi：10.3969/J.ISSN.1672-7274.2024.10.010

中圖分類號(hào)：TP 391.41                 文獻(xiàn)標(biāo)志碼：A            文章編碼：1672-7274（2024）10-00-03

Research on Fault Detection Method for Substation Primary Equipment Based on Deep Convolutional Neural Network

Abstract： This paper designs a substation primary equipment fault detection method： collecting images of the primary equipment in different lighting environments， creating equipment datasets and preprocessing them， and extracting equipment features for detection based on deep convolutional neural networks. After testing， this method can significantly reduce the missed and false alarm rates of primary equipment faults in substations.

Keywords： convolutional neural Network; substation; one device; fault detection

0   引言

變電一次設(shè)備指的是變電站系統(tǒng)中的電源接入、低壓配電、變壓配電設(shè)備等，其能夠?qū)崿F(xiàn)變電站功能。（剩余3768字）