High-voltage circuit breaker mechanical fault diagnosis method and system
The invention discloses a high-voltage circuit breaker mechanical fault diagnosis method and system. The method comprises the following steps: firstly, acquiring a vibration signal of a high-voltage circuit breaker; and then inputting the vibration signal of the high-voltage circuit breaker into a p...
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creator | YAN JING QI MEIRONG WU YANZE SUI GUOQING XU ZHUOFAN ZHANG ZILONG |
description | The invention discloses a high-voltage circuit breaker mechanical fault diagnosis method and system. The method comprises the following steps: firstly, acquiring a vibration signal of a high-voltage circuit breaker; and then inputting the vibration signal of the high-voltage circuit breaker into a pre-constructed adaptive composition graph convolutional neural network, and processing the vibration signal to obtain the fault type of the high-voltage circuit breaker. According to the model provided by the invention, the numerical characteristics and node structure characteristics of mechanical fault signals of the high-voltage circuit breaker can be fully utilized, and the GCN network is adopted to carry out fault identification, so that high-precision robust diagnosis of mechanical faults of the high-voltage circuit breaker is realized.
本发明公开了一种高压断路器机械故障诊断方法及系统,该方法首先获取高压断路器的振动信号;然后将所述高压断路器的振动信号输入预先构建的自适应构图的图卷积神经网络中,并进行处理,获取所述高压断路器的故障类型。本发明提出的模型能够充分利用高压断路器机械故障信号的数值特征和节点结构特征,采用GCN网络进行故障识别,从而实现高压断路器机械故障的高精度鲁棒诊断。 |
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本发明公开了一种高压断路器机械故障诊断方法及系统,该方法首先获取高压断路器的振动信号;然后将所述高压断路器的振动信号输入预先构建的自适应构图的图卷积神经网络中,并进行处理,获取所述高压断路器的故障类型。本发明提出的模型能够充分利用高压断路器机械故障信号的数值特征和节点结构特征,采用GCN网络进行故障识别,从而实现高压断路器机械故障的高精度鲁棒诊断。</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC ORINFRASONIC WAVES ; MEASURING ; MEASURING ELECTRIC VARIABLES ; MEASURING MAGNETIC VARIABLES ; PHYSICS ; TESTING ; TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES ; TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240402&DB=EPODOC&CC=CN&NR=117804759A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25555,76308</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240402&DB=EPODOC&CC=CN&NR=117804759A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>YAN JING</creatorcontrib><creatorcontrib>QI MEIRONG</creatorcontrib><creatorcontrib>WU YANZE</creatorcontrib><creatorcontrib>SUI GUOQING</creatorcontrib><creatorcontrib>XU ZHUOFAN</creatorcontrib><creatorcontrib>ZHANG ZILONG</creatorcontrib><title>High-voltage circuit breaker mechanical fault diagnosis method and system</title><description>The invention discloses a high-voltage circuit breaker mechanical fault diagnosis method and system. The method comprises the following steps: firstly, acquiring a vibration signal of a high-voltage circuit breaker; and then inputting the vibration signal of the high-voltage circuit breaker into a pre-constructed adaptive composition graph convolutional neural network, and processing the vibration signal to obtain the fault type of the high-voltage circuit breaker. According to the model provided by the invention, the numerical characteristics and node structure characteristics of mechanical fault signals of the high-voltage circuit breaker can be fully utilized, and the GCN network is adopted to carry out fault identification, so that high-precision robust diagnosis of mechanical faults of the high-voltage circuit breaker is realized.
本发明公开了一种高压断路器机械故障诊断方法及系统,该方法首先获取高压断路器的振动信号;然后将所述高压断路器的振动信号输入预先构建的自适应构图的图卷积神经网络中,并进行处理,获取所述高压断路器的故障类型。本发明提出的模型能够充分利用高压断路器机械故障信号的数值特征和节点结构特征,采用GCN网络进行故障识别,从而实现高压断路器机械故障的高精度鲁棒诊断。</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC ORINFRASONIC WAVES</subject><subject>MEASURING</subject><subject>MEASURING ELECTRIC VARIABLES</subject><subject>MEASURING MAGNETIC VARIABLES</subject><subject>PHYSICS</subject><subject>TESTING</subject><subject>TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES</subject><subject>TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZPD0yEzP0C3LzylJTE9VSM4sSi7NLFFIKkpNzE4tUshNTc5IzMtMTsxRSEsszSlRSMlMTM_LL84sBkqVZOSnKCTmpSgUVxaXpObyMLCmJeYUp_JCaW4GRTfXEGcP3dSC_PjU4oLE5NS81JJ4Zz9DQ3MLAxNzU0tHY2LUAAD10DTt</recordid><startdate>20240402</startdate><enddate>20240402</enddate><creator>YAN JING</creator><creator>QI MEIRONG</creator><creator>WU YANZE</creator><creator>SUI GUOQING</creator><creator>XU ZHUOFAN</creator><creator>ZHANG ZILONG</creator><scope>EVB</scope></search><sort><creationdate>20240402</creationdate><title>High-voltage circuit breaker mechanical fault diagnosis method and system</title><author>YAN JING ; QI MEIRONG ; WU YANZE ; SUI GUOQING ; XU ZHUOFAN ; ZHANG ZILONG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN117804759A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC ORINFRASONIC WAVES</topic><topic>MEASURING</topic><topic>MEASURING ELECTRIC VARIABLES</topic><topic>MEASURING MAGNETIC VARIABLES</topic><topic>PHYSICS</topic><topic>TESTING</topic><topic>TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES</topic><topic>TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>YAN JING</creatorcontrib><creatorcontrib>QI MEIRONG</creatorcontrib><creatorcontrib>WU YANZE</creatorcontrib><creatorcontrib>SUI GUOQING</creatorcontrib><creatorcontrib>XU ZHUOFAN</creatorcontrib><creatorcontrib>ZHANG ZILONG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>YAN JING</au><au>QI MEIRONG</au><au>WU YANZE</au><au>SUI GUOQING</au><au>XU ZHUOFAN</au><au>ZHANG ZILONG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>High-voltage circuit breaker mechanical fault diagnosis method and system</title><date>2024-04-02</date><risdate>2024</risdate><abstract>The invention discloses a high-voltage circuit breaker mechanical fault diagnosis method and system. The method comprises the following steps: firstly, acquiring a vibration signal of a high-voltage circuit breaker; and then inputting the vibration signal of the high-voltage circuit breaker into a pre-constructed adaptive composition graph convolutional neural network, and processing the vibration signal to obtain the fault type of the high-voltage circuit breaker. According to the model provided by the invention, the numerical characteristics and node structure characteristics of mechanical fault signals of the high-voltage circuit breaker can be fully utilized, and the GCN network is adopted to carry out fault identification, so that high-precision robust diagnosis of mechanical faults of the high-voltage circuit breaker is realized.
本发明公开了一种高压断路器机械故障诊断方法及系统,该方法首先获取高压断路器的振动信号;然后将所述高压断路器的振动信号输入预先构建的自适应构图的图卷积神经网络中,并进行处理,获取所述高压断路器的故障类型。本发明提出的模型能够充分利用高压断路器机械故障信号的数值特征和节点结构特征,采用GCN网络进行故障识别,从而实现高压断路器机械故障的高精度鲁棒诊断。</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC ORINFRASONIC WAVES MEASURING MEASURING ELECTRIC VARIABLES MEASURING MAGNETIC VARIABLES PHYSICS TESTING TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR |
title | High-voltage circuit breaker mechanical fault diagnosis method and system |
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