{"id":"https://openalex.org/W4312244595","doi":"https://doi.org/10.1109/tii.2022.3220847","title":"Semisupervised Machine Fault Diagnosis Fusing Unsupervised Graph Contrastive Learning","display_name":"Semisupervised Machine Fault Diagnosis Fusing Unsupervised Graph Contrastive Learning","publication_year":2022,"publication_date":"2022-11-09","ids":{"openalex":"https://openalex.org/W4312244595","doi":"https://doi.org/10.1109/tii.2022.3220847"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2022.3220847","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2022.3220847","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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/A5017503188","display_name":"Chaoying Yang","orcid":"https://orcid.org/0000-0003-0050-9766"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoying Yang","raw_affiliation_strings":["MOE Key Laboratory of Image Information Processing and Intelligent Control, School of Artificial Intelligence and Automation and the Belt and Road Joint Laboratory on Measurement and Control Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-0050-9766","affiliations":[{"raw_affiliation_string":"MOE Key Laboratory of Image Information Processing and Intelligent Control, School of Artificial Intelligence and Automation and the Belt and Road Joint Laboratory on Measurement and Control Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100454052","display_name":"Jie Liu","orcid":"https://orcid.org/0000-0002-0750-1030"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Liu","raw_affiliation_strings":["School of Civil and Hydraulic Engineering and the Hubei Key Laboratory of Digital River Basin Science and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-0750-1030","affiliations":[{"raw_affiliation_string":"School of Civil and Hydraulic Engineering and the Hubei Key Laboratory of Digital River Basin Science and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015773896","display_name":"Kaibo Zhou","orcid":"https://orcid.org/0000-0003-0055-3193"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaibo Zhou","raw_affiliation_strings":["MOE Key Laboratory of Image Information Processing and Intelligent Control, School of Artificial Intelligence and Automation and the Belt and Road Joint Laboratory on Measurement and Control Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-0055-3193","affiliations":[{"raw_affiliation_string":"MOE Key Laboratory of Image Information Processing and Intelligent Control, School of Artificial Intelligence and Automation and the Belt and Road Joint Laboratory on Measurement and Control Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008653906","display_name":"Xingxing Jiang","orcid":"https://orcid.org/0000-0003-2987-6930"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingxing Jiang","raw_affiliation_strings":["School of Rail Transportation, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2987-6930","affiliations":[{"raw_affiliation_string":"School of Rail Transportation, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9364,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.94409394,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"19","issue":"8","first_page":"8644","last_page":"8653"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9544000029563904,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9514999985694885,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6449814438819885},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6155716180801392},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5588939189910889},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.548759937286377},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5222693085670471},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5141289830207825},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5090138912200928},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.501413106918335},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44280192255973816},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.17334750294685364}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6449814438819885},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6155716180801392},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5588939189910889},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.548759937286377},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5222693085670471},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5141289830207825},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5090138912200928},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.501413106918335},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44280192255973816},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.17334750294685364},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2022.3220847","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2022.3220847","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2012272686","display_name":null,"funder_award_id":"52205104","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2940249851","display_name":"\u57fa\u4e8e\u78c1\u7eb3\u7c73\u7c92\u5b50\u7684\u6cb9\u85cf\u4f20\u611f\u548c\u7535\u78c1\u6210\u50cf\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61873101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2102661631","https://openalex.org/W2590822257","https://openalex.org/W2897135094","https://openalex.org/W2943389092","https://openalex.org/W2963521811","https://openalex.org/W2964015378","https://openalex.org/W2964321699","https://openalex.org/W2985331920","https://openalex.org/W2998970859","https://openalex.org/W3005486352","https://openalex.org/W3007619185","https://openalex.org/W3033039844","https://openalex.org/W3095602948","https://openalex.org/W3095770430","https://openalex.org/W3133696297","https://openalex.org/W3135448057","https://openalex.org/W3137410503","https://openalex.org/W3138513656","https://openalex.org/W3157039246","https://openalex.org/W3157123770","https://openalex.org/W3187966659","https://openalex.org/W3197165562","https://openalex.org/W3197457608","https://openalex.org/W3208157985","https://openalex.org/W3208271024","https://openalex.org/W3213543645","https://openalex.org/W4200473862","https://openalex.org/W4200534047","https://openalex.org/W4205400837","https://openalex.org/W4297733535","https://openalex.org/W4385245566","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6739901393","https://openalex.org/W6755573351","https://openalex.org/W6779940601","https://openalex.org/W6783243524","https://openalex.org/W6784694379","https://openalex.org/W6790690058","https://openalex.org/W6803811376"],"related_works":["https://openalex.org/W3174759195","https://openalex.org/W3167013339","https://openalex.org/W4287121366","https://openalex.org/W60493759","https://openalex.org/W4309346246","https://openalex.org/W4386437125","https://openalex.org/W4308619659","https://openalex.org/W3213069564","https://openalex.org/W2997229301","https://openalex.org/W2785325870"],"abstract_inverted_index":{"By":[0],"learning":[1,45,95,113,131],"effective":[2],"information":[3],"from":[4],"unlabeled":[5,20],"nodes,":[6,21],"node-level":[7],"graph":[8,25,43,69,111,129],"data-driven":[9],"diagnosis":[10,40],"methods":[11],"perform":[12],"better":[13],"than":[14],"graph-level":[15],"methods.":[16],"However,":[17],"features":[18],"of":[19,96],"indirectly":[22],"involved":[23],"in":[24],"feature":[26,112,130],"learning,":[27],"are":[28,58],"not":[29],"fully":[30],"utilized.":[31],"To":[32],"overcome":[33],"aforementioned":[34],"limitations,":[35],"a":[36,74,79,84,146],"semisupervised":[37,110],"machine":[38],"fault":[39],"fusing":[41],"unsupervised":[42,86,105],"contrastive":[44],"(GCL)":[46],"is":[47,65,89,101,117],"proposed.":[48],"A":[49],"new":[50,75,85],"GCL":[51,87,106],"framework,":[52],"where":[53,125],"positive":[54,97],"and":[55,83,98,138],"negative":[56,99],"graphs":[57,100,116],"generated":[59],"by":[60,103,120],"calculating":[61],"Pearson":[62],"correlation":[63],"coefficient,":[64],"fused":[66],"into":[67],"the":[68,104,109,121,126,142],"transformer":[70],"network":[71],"(GTN).":[72],"Furthermore,":[73],"combined":[76],"loss,":[77,88,124],"including":[78],"supervised":[80,122],"cross-entropy":[81,123],"loss":[82],"designed":[90],"for":[91,114,128],"GTN":[92,127],"training.":[93],"Contrastive":[94],"guided":[102],"loss.":[107],"While":[108],"original":[115],"mainly":[118],"driven":[119],"shares":[132],"parameters.":[133],"Experimental":[134],"results":[135],"on":[136],"public":[137],"real":[139],"datasets":[140],"show":[141],"proposed":[143],"method":[144],"achieves":[145],"competitive":[147],"performance.":[148]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
