{"id":"https://openalex.org/W4405786362","doi":"https://doi.org/10.1109/tim.2024.3522658","title":"Unsupervised Diagnosis of Interturn Short Circuit of Permanent Magnet Synchronous Motor Guided by Density-Based Clustering and Deep Learning","display_name":"Unsupervised Diagnosis of Interturn Short Circuit of Permanent Magnet Synchronous Motor Guided by Density-Based Clustering and Deep Learning","publication_year":2024,"publication_date":"2024-12-25","ids":{"openalex":"https://openalex.org/W4405786362","doi":"https://doi.org/10.1109/tim.2024.3522658"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2024.3522658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3522658","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/A5103871296","display_name":"Xiang Wu","orcid":"https://orcid.org/0009-0002-2158-188X"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiang Wu","raw_affiliation_strings":["College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100780141","display_name":"Minglei Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minglei Li","raw_affiliation_strings":["College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002615730","display_name":"Yanfeng Geng","orcid":"https://orcid.org/0000-0001-8184-0041"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanfeng Geng","raw_affiliation_strings":["College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061927035","display_name":"Haiyu Qian","orcid":"https://orcid.org/0009-0003-6060-5407"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyu Qian","raw_affiliation_strings":["College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103871296"],"corresponding_institution_ids":["https://openalex.org/I4210162190"],"apc_list":null,"apc_paid":null,"fwci":1.1797,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.77560946,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"74","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11222","display_name":"Magnetic Properties and Applications","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2504","display_name":"Electronic, Optical and Magnetic Materials"},"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/T11222","display_name":"Magnetic Properties and Applications","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2504","display_name":"Electronic, Optical and Magnetic Materials"},"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/T10278","display_name":"Electric Motor Design and Analysis","score":0.987500011920929,"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"}},{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/cluster-analysis","display_name":"Cluster analysis","score":0.7029814720153809},{"id":"https://openalex.org/keywords/magnet","display_name":"Magnet","score":0.5630131363868713},{"id":"https://openalex.org/keywords/synchronous-motor","display_name":"Synchronous motor","score":0.5155289173126221},{"id":"https://openalex.org/keywords/turn","display_name":"Turn (biochemistry)","score":0.5133237242698669},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4631343185901642},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46204233169555664},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4278213083744049},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33062422275543213},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3212395906448364},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.29903444647789},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.26751524209976196},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.20520532131195068},{"id":"https://openalex.org/keywords/nuclear-magnetic-resonance","display_name":"Nuclear magnetic resonance","score":0.123210608959198}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7029814720153809},{"id":"https://openalex.org/C16389437","wikidata":"https://www.wikidata.org/wiki/Q11421","display_name":"Magnet","level":2,"score":0.5630131363868713},{"id":"https://openalex.org/C71376005","wikidata":"https://www.wikidata.org/wiki/Q845675","display_name":"Synchronous motor","level":2,"score":0.5155289173126221},{"id":"https://openalex.org/C85641259","wikidata":"https://www.wikidata.org/wiki/Q290042","display_name":"Turn (biochemistry)","level":2,"score":0.5133237242698669},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4631343185901642},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46204233169555664},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4278213083744049},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33062422275543213},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3212395906448364},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.29903444647789},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26751524209976196},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.20520532131195068},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.123210608959198}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2024.3522658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3522658","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/G4788907491","display_name":null,"funder_award_id":"22CX06035A","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5538130892","display_name":null,"funder_award_id":"ZR2020MA056","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G7308361541","display_name":null,"funder_award_id":"62033008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7394117417","display_name":null,"funder_award_id":"62203467","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"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2028119131","https://openalex.org/W2060304859","https://openalex.org/W2128728535","https://openalex.org/W2153504150","https://openalex.org/W2582337578","https://openalex.org/W2768753204","https://openalex.org/W2805113141","https://openalex.org/W2813911573","https://openalex.org/W2883725317","https://openalex.org/W2886794804","https://openalex.org/W2898375427","https://openalex.org/W2995140071","https://openalex.org/W3000409346","https://openalex.org/W3010877614","https://openalex.org/W3045010471","https://openalex.org/W3106655088","https://openalex.org/W3133192086","https://openalex.org/W3139011613","https://openalex.org/W3209651137","https://openalex.org/W4225166154","https://openalex.org/W4309047247","https://openalex.org/W4312695356","https://openalex.org/W4318486229","https://openalex.org/W4324383801","https://openalex.org/W4367663517","https://openalex.org/W4372215235","https://openalex.org/W4380635141","https://openalex.org/W4382203600","https://openalex.org/W4387010320","https://openalex.org/W4389891326","https://openalex.org/W4390692066","https://openalex.org/W4391088299","https://openalex.org/W4391123281","https://openalex.org/W4391287908","https://openalex.org/W4399654715","https://openalex.org/W4400645360"],"related_works":["https://openalex.org/W4231070408","https://openalex.org/W943151747","https://openalex.org/W2048981943","https://openalex.org/W2753901553","https://openalex.org/W2804368879","https://openalex.org/W4245567755","https://openalex.org/W2325174796","https://openalex.org/W2798522476","https://openalex.org/W4253040403","https://openalex.org/W4206663386"],"abstract_inverted_index":{"The":[0,88,158],"operational":[1],"efficiency":[2],"of":[3,20,51,139,177,184,192],"a":[4,48,92,166],"permanent":[5],"magnet":[6],"synchronous":[7],"motor":[8],"(PMSM)":[9],"is":[10,58,125],"intrinsically":[11],"linked":[12],"to":[13,35,54,60,102,141,150],"its":[14,39],"stability,":[15],"making":[16],"the":[17,36,98,104,152,162,171,182,185,193],"accurate":[18],"diagnosis":[19,44,79],"common":[21],"faults":[22,191],"such":[23],"as":[24],"interturn":[25],"short":[26],"circuits":[27],"(ITSCs)":[28],"crucial.":[29],"ITSC":[30,77,142,190],"can":[31],"cause":[32],"significant":[33],"damage":[34],"PMSM":[37,145],"and":[38,97,170],"system.":[40],"Traditional":[41],"data-driven":[42],"fault":[43,78],"methods":[45],"often":[46],"require":[47],"large":[49],"amount":[50],"expert-labeled":[52],"data":[53,83,94,111],"ensure":[55],"accuracy,":[56],"which":[57,128],"challenging":[59],"obtain":[61],"in":[62,127,155,188],"actual":[63],"operations.":[64],"To":[65],"address":[66],"this,":[67,114],"this":[68,156],"article":[69],"introduces":[70],"an":[71,115,175],"unsupervised":[72,116],"learning":[73],"(UL)":[74],"method":[75,96,153,186],"for":[76,132],"that":[80],"extracts":[81],"inherent":[82],"patterns":[84],"from":[85],"unlabeled":[86],"samples.":[87],"approach":[89],"begins":[90],"with":[91,122],"unique":[93],"processing":[95],"fast":[99],"Fourier":[100],"transform":[101],"handle":[103],"original":[105],"three-phase":[106],"current":[107],"data,":[108],"thereby":[109],"reducing":[110],"complexity.":[112],"Following":[113],"framework,":[117],"utilizing":[118],"noise-aware":[119],"density-based":[120],"clustering":[121],"auto-tuning":[123],"(NADCAT),":[124],"constructed,":[126],"NADCAT":[129,164],"provides":[130],"pseudo-labels":[131,159],"deep":[133],"neural":[134],"networks,":[135],"enabling":[136],"precise":[137],"mapping":[138],"features":[140],"faults.":[143],"A":[144],"experiment":[146],"platform":[147],"was":[148],"established":[149],"validate":[151],"proposed":[154,163,187],"article.":[157],"obtained":[160],"by":[161],"achieved":[165],"92.8%":[167],"effective":[168],"rate,":[169],"diagnostic":[172],"model":[173],"attained":[174],"accuracy":[176],"97.63%.":[178],"These":[179],"results":[180],"demonstrate":[181],"effectiveness":[183],"diagnosing":[189],"PMSM.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
