Transformer substation fault analysis and early warning method and device, storage medium and electronic equipment

The invention relates to the technical field of transformer substation fault monitoring, in particular to a transformer substation fault analysis and early warning method and device, a storage medium and electronic equipment, and the method comprises the steps: carrying out the feature selection of...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: GAO CONG, SHEN XIAOYONG, XIA YONGPING, MAJNI, TOLIVBEK, MAIMAITI NOOR, QU XIANGYUN, ZHU MENGYAO, CHENG PEIZHONG, YANG YANPING, GUO TINGJIN, DUAN PENGFEI, XU JIANYING, ZHENG YINGYING, XU LIN, YU XIANGTAO
Format: Patent
Sprache:chi ; eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator GAO CONG
SHEN XIAOYONG
XIA YONGPING
MAJNI, TOLIVBEK
MAIMAITI NOOR
QU XIANGYUN
ZHU MENGYAO
CHENG PEIZHONG
YANG YANPING
GUO TINGJIN
DUAN PENGFEI
XU JIANYING
ZHENG YINGYING
XU LIN
YU XIANGTAO
description The invention relates to the technical field of transformer substation fault monitoring, in particular to a transformer substation fault analysis and early warning method and device, a storage medium and electronic equipment, and the method comprises the steps: carrying out the feature selection of to-be-analyzed transformer substation fault data through employing a Boruta algorithm; inputting the to-be-analyzed transformer substation fault data features after feature selection into a fault prediction model, and outputting a corresponding transformer substation fault; and inputting the transformer substation fault into the risk judgment model for fault risk level prediction. According to the method, the Boruta algorithm is used for carrying out feature selection on the transformer substation fault data, the data set dimension and the calculation complexity are reduced, the extreme learning machine is used for carrying out transformer substation fault prediction, and the Markov chain and the fuzzy matrix are c
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN118627884A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN118627884A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN118627884A3</originalsourceid><addsrcrecordid>eNqNizEOwjAMRbswIOAOYYehgKArqkBMTN0rk7olUuIU2wH19lTAAZjel95_04wrBpI2ckA2km6ioC6SaSF5NUDgB3EyjsYgsB_MC5gcdSag3mPzEQ0-ncWVEY0MHY6qcSl8G49WOZKzBh_J9QFJ59mkBS-4-HGWLc-nqryssY81Sg8WCbUur3le7DeHotgdt_983lxnRNE</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Transformer substation fault analysis and early warning method and device, storage medium and electronic equipment</title><source>esp@cenet</source><creator>GAO CONG ; SHEN XIAOYONG ; XIA YONGPING ; MAJNI, TOLIVBEK ; MAIMAITI NOOR ; QU XIANGYUN ; ZHU MENGYAO ; CHENG PEIZHONG ; YANG YANPING ; GUO TINGJIN ; DUAN PENGFEI ; XU JIANYING ; ZHENG YINGYING ; XU LIN ; YU XIANGTAO</creator><creatorcontrib>GAO CONG ; SHEN XIAOYONG ; XIA YONGPING ; MAJNI, TOLIVBEK ; MAIMAITI NOOR ; QU XIANGYUN ; ZHU MENGYAO ; CHENG PEIZHONG ; YANG YANPING ; GUO TINGJIN ; DUAN PENGFEI ; XU JIANYING ; ZHENG YINGYING ; XU LIN ; YU XIANGTAO</creatorcontrib><description>The invention relates to the technical field of transformer substation fault monitoring, in particular to a transformer substation fault analysis and early warning method and device, a storage medium and electronic equipment, and the method comprises the steps: carrying out the feature selection of to-be-analyzed transformer substation fault data through employing a Boruta algorithm; inputting the to-be-analyzed transformer substation fault data features after feature selection into a fault prediction model, and outputting a corresponding transformer substation fault; and inputting the transformer substation fault into the risk judgment model for fault risk level prediction. According to the method, the Boruta algorithm is used for carrying out feature selection on the transformer substation fault data, the data set dimension and the calculation complexity are reduced, the extreme learning machine is used for carrying out transformer substation fault prediction, and the Markov chain and the fuzzy matrix are c</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, 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&amp;date=20240910&amp;DB=EPODOC&amp;CC=CN&amp;NR=118627884A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20240910&amp;DB=EPODOC&amp;CC=CN&amp;NR=118627884A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>GAO CONG</creatorcontrib><creatorcontrib>SHEN XIAOYONG</creatorcontrib><creatorcontrib>XIA YONGPING</creatorcontrib><creatorcontrib>MAJNI, TOLIVBEK</creatorcontrib><creatorcontrib>MAIMAITI NOOR</creatorcontrib><creatorcontrib>QU XIANGYUN</creatorcontrib><creatorcontrib>ZHU MENGYAO</creatorcontrib><creatorcontrib>CHENG PEIZHONG</creatorcontrib><creatorcontrib>YANG YANPING</creatorcontrib><creatorcontrib>GUO TINGJIN</creatorcontrib><creatorcontrib>DUAN PENGFEI</creatorcontrib><creatorcontrib>XU JIANYING</creatorcontrib><creatorcontrib>ZHENG YINGYING</creatorcontrib><creatorcontrib>XU LIN</creatorcontrib><creatorcontrib>YU XIANGTAO</creatorcontrib><title>Transformer substation fault analysis and early warning method and device, storage medium and electronic equipment</title><description>The invention relates to the technical field of transformer substation fault monitoring, in particular to a transformer substation fault analysis and early warning method and device, a storage medium and electronic equipment, and the method comprises the steps: carrying out the feature selection of to-be-analyzed transformer substation fault data through employing a Boruta algorithm; inputting the to-be-analyzed transformer substation fault data features after feature selection into a fault prediction model, and outputting a corresponding transformer substation fault; and inputting the transformer substation fault into the risk judgment model for fault risk level prediction. According to the method, the Boruta algorithm is used for carrying out feature selection on the transformer substation fault data, the data set dimension and the calculation complexity are reduced, the extreme learning machine is used for carrying out transformer substation fault prediction, and the Markov chain and the fuzzy matrix are c</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNizEOwjAMRbswIOAOYYehgKArqkBMTN0rk7olUuIU2wH19lTAAZjel95_04wrBpI2ckA2km6ioC6SaSF5NUDgB3EyjsYgsB_MC5gcdSag3mPzEQ0-ncWVEY0MHY6qcSl8G49WOZKzBh_J9QFJ59mkBS-4-HGWLc-nqryssY81Sg8WCbUur3le7DeHotgdt_983lxnRNE</recordid><startdate>20240910</startdate><enddate>20240910</enddate><creator>GAO CONG</creator><creator>SHEN XIAOYONG</creator><creator>XIA YONGPING</creator><creator>MAJNI, TOLIVBEK</creator><creator>MAIMAITI NOOR</creator><creator>QU XIANGYUN</creator><creator>ZHU MENGYAO</creator><creator>CHENG PEIZHONG</creator><creator>YANG YANPING</creator><creator>GUO TINGJIN</creator><creator>DUAN PENGFEI</creator><creator>XU JIANYING</creator><creator>ZHENG YINGYING</creator><creator>XU LIN</creator><creator>YU XIANGTAO</creator><scope>EVB</scope></search><sort><creationdate>20240910</creationdate><title>Transformer substation fault analysis and early warning method and device, storage medium and electronic equipment</title><author>GAO CONG ; SHEN XIAOYONG ; XIA YONGPING ; MAJNI, TOLIVBEK ; MAIMAITI NOOR ; QU XIANGYUN ; ZHU MENGYAO ; CHENG PEIZHONG ; YANG YANPING ; GUO TINGJIN ; DUAN PENGFEI ; XU JIANYING ; ZHENG YINGYING ; XU LIN ; YU XIANGTAO</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN118627884A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>GAO CONG</creatorcontrib><creatorcontrib>SHEN XIAOYONG</creatorcontrib><creatorcontrib>XIA YONGPING</creatorcontrib><creatorcontrib>MAJNI, TOLIVBEK</creatorcontrib><creatorcontrib>MAIMAITI NOOR</creatorcontrib><creatorcontrib>QU XIANGYUN</creatorcontrib><creatorcontrib>ZHU MENGYAO</creatorcontrib><creatorcontrib>CHENG PEIZHONG</creatorcontrib><creatorcontrib>YANG YANPING</creatorcontrib><creatorcontrib>GUO TINGJIN</creatorcontrib><creatorcontrib>DUAN PENGFEI</creatorcontrib><creatorcontrib>XU JIANYING</creatorcontrib><creatorcontrib>ZHENG YINGYING</creatorcontrib><creatorcontrib>XU LIN</creatorcontrib><creatorcontrib>YU XIANGTAO</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>GAO CONG</au><au>SHEN XIAOYONG</au><au>XIA YONGPING</au><au>MAJNI, TOLIVBEK</au><au>MAIMAITI NOOR</au><au>QU XIANGYUN</au><au>ZHU MENGYAO</au><au>CHENG PEIZHONG</au><au>YANG YANPING</au><au>GUO TINGJIN</au><au>DUAN PENGFEI</au><au>XU JIANYING</au><au>ZHENG YINGYING</au><au>XU LIN</au><au>YU XIANGTAO</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Transformer substation fault analysis and early warning method and device, storage medium and electronic equipment</title><date>2024-09-10</date><risdate>2024</risdate><abstract>The invention relates to the technical field of transformer substation fault monitoring, in particular to a transformer substation fault analysis and early warning method and device, a storage medium and electronic equipment, and the method comprises the steps: carrying out the feature selection of to-be-analyzed transformer substation fault data through employing a Boruta algorithm; inputting the to-be-analyzed transformer substation fault data features after feature selection into a fault prediction model, and outputting a corresponding transformer substation fault; and inputting the transformer substation fault into the risk judgment model for fault risk level prediction. According to the method, the Boruta algorithm is used for carrying out feature selection on the transformer substation fault data, the data set dimension and the calculation complexity are reduced, the extreme learning machine is used for carrying out transformer substation fault prediction, and the Markov chain and the fuzzy matrix are c</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language chi ; eng
recordid cdi_epo_espacenet_CN118627884A
source esp@cenet
subjects CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
title Transformer substation fault analysis and early warning method and device, storage medium and electronic equipment
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-09T07%3A29%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=GAO%20CONG&rft.date=2024-09-10&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN118627884A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true