{"id":"https://openalex.org/W4226063738","doi":"https://doi.org/10.1109/tim.2022.3160543","title":"Gas-Insulated Switchgear Insulation Defect Diagnosis via a Novel Domain Adaptive Graph Convolutional Network","display_name":"Gas-Insulated Switchgear Insulation Defect Diagnosis via a Novel Domain Adaptive Graph Convolutional Network","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4226063738","doi":"https://doi.org/10.1109/tim.2022.3160543"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3160543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3160543","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083417541","display_name":"Yanxin Wang","orcid":"https://orcid.org/0000-0002-4105-7172"},"institutions":[{"id":"https://openalex.org/I4391768273","display_name":"State Key Laboratory of Electrical Insulation and Power Equipment","ror":"https://ror.org/03kd9rr37","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391768273","https://openalex.org/I87445476"]},{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanxin Wang","raw_affiliation_strings":["Department of Electrical Engineering, State Key Laboratory of Electrical Insulation and Power Equipment, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-4105-7172","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, State Key Laboratory of Electrical Insulation and Power Equipment, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476","https://openalex.org/I4391768273"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077575255","display_name":"Jing Yan","orcid":"https://orcid.org/0000-0002-8456-2056"},"institutions":[{"id":"https://openalex.org/I4391768273","display_name":"State Key Laboratory of Electrical Insulation and Power Equipment","ror":"https://ror.org/03kd9rr37","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391768273","https://openalex.org/I87445476"]},{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Yan","raw_affiliation_strings":["Department of Electrical Engineering, State Key Laboratory of Electrical Insulation and Power Equipment, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-8456-2056","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, State Key Laboratory of Electrical Insulation and Power Equipment, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476","https://openalex.org/I4391768273"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103110757","display_name":"Zhou Yang","orcid":"https://orcid.org/0000-0002-3041-3813"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhou Yang","raw_affiliation_strings":["Department of Computer Science, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-3041-3813","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054858647","display_name":"Zhenkang Qi","orcid":"https://orcid.org/0000-0002-7147-2107"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenkang Qi","raw_affiliation_strings":["State Key Laboratory of Power System and Generation Equipment, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7147-2107","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Power System and Generation Equipment, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100420050","display_name":"Jianhua Wang","orcid":"https://orcid.org/0000-0003-0560-2556"},"institutions":[{"id":"https://openalex.org/I4391768273","display_name":"State Key Laboratory of Electrical Insulation and Power Equipment","ror":"https://ror.org/03kd9rr37","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391768273","https://openalex.org/I87445476"]},{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Wang","raw_affiliation_strings":["Department of Electrical Engineering, State Key Laboratory of Electrical Insulation and Power Equipment, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0003-0560-2556","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, State Key Laboratory of Electrical Insulation and Power Equipment, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476","https://openalex.org/I4391768273"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054775292","display_name":"Yingsan Geng","orcid":"https://orcid.org/0000-0002-7040-5471"},"institutions":[{"id":"https://openalex.org/I4391768273","display_name":"State Key Laboratory of Electrical Insulation and Power Equipment","ror":"https://ror.org/03kd9rr37","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391768273","https://openalex.org/I87445476"]},{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingsan Geng","raw_affiliation_strings":["Department of Electrical Engineering, State Key Laboratory of Electrical Insulation and Power Equipment, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-7040-5471","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, State Key Laboratory of Electrical Insulation and Power Equipment, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476","https://openalex.org/I4391768273"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8849,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.85391233,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10511","display_name":"High voltage insulation and dielectric phenomena","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10511","display_name":"High voltage insulation and dielectric phenomena","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.975600004196167,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11941","display_name":"Power System Reliability and Maintenance","score":0.9700000286102295,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/switchgear","display_name":"Switchgear","score":0.8188654184341431},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6209938526153564},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.612591028213501},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.585419237613678},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5771809816360474},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5224651098251343},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5085703134536743},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46599069237709045},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4615035653114319},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.45882463455200195},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44273626804351807},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3214980959892273},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21869608759880066},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18221032619476318},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.14357540011405945},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.07698041200637817}],"concepts":[{"id":"https://openalex.org/C93893174","wikidata":"https://www.wikidata.org/wiki/Q1273786","display_name":"Switchgear","level":2,"score":0.8188654184341431},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6209938526153564},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.612591028213501},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.585419237613678},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5771809816360474},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5224651098251343},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5085703134536743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46599069237709045},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4615035653114319},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.45882463455200195},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44273626804351807},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3214980959892273},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21869608759880066},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18221032619476318},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.14357540011405945},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.07698041200637817},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2022.3160543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3160543","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8688953559","display_name":null,"funder_award_id":"5500-202199527A-0-5-ZN","funder_id":"https://openalex.org/F4320326707","funder_display_name":"State Grid Corporation of China"}],"funders":[{"id":"https://openalex.org/F4320326707","display_name":"State Grid Corporation of China","ror":"https://ror.org/05twwhs70"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W964460774","https://openalex.org/W1986614398","https://openalex.org/W2798199013","https://openalex.org/W2798915202","https://openalex.org/W2808408933","https://openalex.org/W2889767715","https://openalex.org/W2897536120","https://openalex.org/W2904900486","https://openalex.org/W2939208918","https://openalex.org/W2954894921","https://openalex.org/W2963214104","https://openalex.org/W2989675056","https://openalex.org/W2996091850","https://openalex.org/W3005486352","https://openalex.org/W3007050866","https://openalex.org/W3011667710","https://openalex.org/W3012644407","https://openalex.org/W3018957240","https://openalex.org/W3023514908","https://openalex.org/W3081123675","https://openalex.org/W3088855320","https://openalex.org/W3108847889","https://openalex.org/W3110385569","https://openalex.org/W3110510730","https://openalex.org/W3110754121","https://openalex.org/W3128994661","https://openalex.org/W3138809170","https://openalex.org/W3153068647","https://openalex.org/W3157123770","https://openalex.org/W3167703259","https://openalex.org/W3185972919","https://openalex.org/W3205146642","https://openalex.org/W3205895886","https://openalex.org/W6761665040","https://openalex.org/W6771510844","https://openalex.org/W6781851036","https://openalex.org/W6796495850"],"related_works":["https://openalex.org/W4385415357","https://openalex.org/W4312417841","https://openalex.org/W2811390910","https://openalex.org/W2146076056","https://openalex.org/W4312376745","https://openalex.org/W2767651786","https://openalex.org/W2144059113","https://openalex.org/W2772780115","https://openalex.org/W2385132419","https://openalex.org/W1977222486"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"have":[4],"promoted":[5],"the":[6,28,31,35,47,83,96,99,103,108,112,117,124,139,146,149,155,162],"development":[7],"of":[8,17,34,95,102,111,154,195],"insulation":[9,79,113,127,198],"defect":[10,80,114,128,199],"diagnosis":[11,129,194],"for":[12,77,190],"gas-insulated":[13],"switchgear":[14],"(GIS)":[15],"because":[16],"their":[18],"excellent":[19],"feature":[20,36,41,104,163],"extraction":[21],"and":[22,45,56,86,151,157,175,192],"classification":[23],"capabilities.":[24],"However,":[25],"CNN":[26],"ignores":[27],"correlation":[29,97],"between":[30,98,138,148],"local":[32,100],"areas":[33,101],"space,":[37],"resulting":[38],"in":[39,50,181],"insufficient":[40],"utilization.":[42],"Moreover,":[43],"deploying":[44],"applying":[46],"methods":[48],"explored":[49],"massive":[51],"laboratory":[52],"data":[53],"to":[54,92,123],"complex":[55],"few-shot":[57,183,196],"conditions":[58],"on-site":[59,125],"is":[60,121,142],"a":[61,69,187],"difficult":[62],"problem":[63],"currently.":[64],"Therefore,":[65],"this":[66],"study":[67],"proposes":[68],"novel":[70],"domain":[71,131],"adaptation":[72],"graph":[73,84,87],"convolutional":[74],"network":[75,89],"(DAGCN)":[76],"GIS":[78,126,197],"diagnosis.":[81,200],"First,":[82],"signal":[85],"convolution":[88],"are":[90],"used":[91],"take":[93],"advantage":[94],"space":[105],"while":[106],"employing":[107],"numerical":[109],"characteristics":[110],"signal.":[115],"Then,":[116],"learned":[118],"diagnostic":[119,173],"method":[120],"deployed":[122],"with":[130],"adaptive":[132],"transfer":[133],"learning":[134],"(TL).":[135],"The":[136,165],"difference":[137,147],"two":[140],"tasks":[141],"reduced":[143],"by":[144],"minimizing":[145],"marginal":[150],"conditional":[152],"distributions":[153],"source":[156],"target":[158],"domains,":[159],"thus,":[160],"realizing":[161],"migration.":[164],"experimental":[166],"verification":[167],"shows":[168],"that":[169],"DAGCN":[170],"has":[171],"higher":[172],"accuracy":[174],"robustness":[176],"than":[177],"traditional":[178],"methods,":[179],"especially":[180],"diagnosing":[182],"on-site.":[184],"It":[185],"provides":[186],"reliable":[188],"reference":[189],"high-precision":[191],"robust":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
