{"id":"https://openalex.org/W4410427575","doi":"https://doi.org/10.1109/tr.2025.3566231","title":"A Novel Transfer Learning Framework Based on Deep Contrastive Convolution for Wind Turbine Bearing Fault Localization","display_name":"A Novel Transfer Learning Framework Based on Deep Contrastive Convolution for Wind Turbine Bearing Fault Localization","publication_year":2025,"publication_date":"2025-05-16","ids":{"openalex":"https://openalex.org/W4410427575","doi":"https://doi.org/10.1109/tr.2025.3566231"},"language":"en","primary_location":{"id":"doi:10.1109/tr.2025.3566231","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2025.3566231","pdf_url":null,"source":{"id":"https://openalex.org/S87725633","display_name":"IEEE Transactions on Reliability","issn_l":"0018-9529","issn":["0018-9529","1558-1721"],"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 Reliability","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/A5101832831","display_name":"Hao Su","orcid":"https://orcid.org/0000-0003-1721-1894"},"institutions":[{"id":"https://openalex.org/I4210165547","display_name":"Dezhou University","ror":"https://ror.org/05mnjs436","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210165547"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Su","raw_affiliation_strings":["School of Energy and Machinery, Dezhou University, Dezhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1721-1894","affiliations":[{"raw_affiliation_string":"School of Energy and Machinery, Dezhou University, Dezhou, China","institution_ids":["https://openalex.org/I4210165547"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073769395","display_name":"Qingtao Yao","orcid":"https://orcid.org/0000-0003-3080-8230"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingtao Yao","raw_affiliation_strings":["Department of Mechanical Engineering, North China Electric Power University, Baoding, China"],"raw_orcid":"https://orcid.org/0000-0003-3080-8230","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066661675","display_name":"Xianze Li","orcid":"https://orcid.org/0000-0002-7566-9847"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianze Li","raw_affiliation_strings":["Department of Mechanical Engineering, North China Electric Power University, Baoding, China"],"raw_orcid":"https://orcid.org/0000-0002-7566-9847","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002789209","display_name":"Ling Xiang","orcid":"https://orcid.org/0000-0002-8309-1977"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Xiang","raw_affiliation_strings":["Department of Mechanical Engineering, North China Electric Power University, Baoding, China"],"raw_orcid":"https://orcid.org/0000-0002-8309-1977","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009818308","display_name":"Aijun Hu","orcid":"https://orcid.org/0000-0003-2844-671X"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aijun Hu","raw_affiliation_strings":["Department of Mechanical Engineering, North China Electric Power University, Baoding, China"],"raw_orcid":"https://orcid.org/0000-0003-2844-671X","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I153473198"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101832831"],"corresponding_institution_ids":["https://openalex.org/I4210165547"],"apc_list":null,"apc_paid":null,"fwci":1.0546,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7623352,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"74","issue":"4","first_page":"5579","last_page":"5591"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.9757000207901001,"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/convolution","display_name":"Convolution (computer science)","score":0.6822163462638855},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5851986408233643},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.5670466423034668},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5351427793502808},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5073511004447937},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4488081932067871},{"id":"https://openalex.org/keywords/turbine","display_name":"Turbine","score":0.4359055161476135},{"id":"https://openalex.org/keywords/transfer-function","display_name":"Transfer function","score":0.43273138999938965},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.4184116721153259},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.32177460193634033},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24578088521957397},{"id":"https://openalex.org/keywords/seismology","display_name":"Seismology","score":0.2189376950263977},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13434800505638123},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.10006445646286011},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.08139598369598389}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6822163462638855},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5851986408233643},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.5670466423034668},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5351427793502808},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5073511004447937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4488081932067871},{"id":"https://openalex.org/C2778449969","wikidata":"https://www.wikidata.org/wiki/Q130760","display_name":"Turbine","level":2,"score":0.4359055161476135},{"id":"https://openalex.org/C81299745","wikidata":"https://www.wikidata.org/wiki/Q334269","display_name":"Transfer function","level":2,"score":0.43273138999938965},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.4184116721153259},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.32177460193634033},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24578088521957397},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.2189376950263977},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13434800505638123},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.10006445646286011},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.08139598369598389}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tr.2025.3566231","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2025.3566231","pdf_url":null,"source":{"id":"https://openalex.org/S87725633","display_name":"IEEE Transactions on Reliability","issn_l":"0018-9529","issn":["0018-9529","1558-1721"],"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 Reliability","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2763907376","https://openalex.org/W2898375427","https://openalex.org/W2915423430","https://openalex.org/W2946048316","https://openalex.org/W2962239755","https://openalex.org/W2998506103","https://openalex.org/W2999406639","https://openalex.org/W3012040475","https://openalex.org/W3039216919","https://openalex.org/W3041218800","https://openalex.org/W3045841679","https://openalex.org/W3095042947","https://openalex.org/W3113310630","https://openalex.org/W3121088397","https://openalex.org/W3177151237","https://openalex.org/W3201753566","https://openalex.org/W3205301901","https://openalex.org/W3209564648","https://openalex.org/W3214164781","https://openalex.org/W4206146696","https://openalex.org/W4206495689","https://openalex.org/W4211227515","https://openalex.org/W4226092012","https://openalex.org/W4285204528","https://openalex.org/W4285231711","https://openalex.org/W4285678828","https://openalex.org/W4304114242","https://openalex.org/W4317038442","https://openalex.org/W4388378537","https://openalex.org/W4391472533","https://openalex.org/W4399313584","https://openalex.org/W4402328060"],"related_works":["https://openalex.org/W2035937180","https://openalex.org/W3196220745","https://openalex.org/W3201126466","https://openalex.org/W4311624988","https://openalex.org/W2061308401","https://openalex.org/W4232403546","https://openalex.org/W2364348613","https://openalex.org/W2366782036","https://openalex.org/W2033726186","https://openalex.org/W3037331970"],"abstract_inverted_index":{"Significant":[0],"advancements":[1],"have":[2],"been":[3,53],"achieved":[4],"in":[5,186],"the":[6,14,25,40,45,48,92,105,113,145,151],"realm":[7],"of":[8,16,47,56,144],"wind":[9,152,187],"turbine":[10,153,188],"fault":[11,159,168,190],"diagnosis":[12],"through":[13],"application":[15],"deep":[17,49,63,69,102],"learning.":[18],"However,":[19],"most":[20],"methods":[21],"generally":[22],"assume":[23],"that":[24,164],"distribution":[26],"between":[27,120],"training":[28],"samples":[29,32],"and":[30,75,88,175],"testing":[31],"remains":[33],"consistent,":[34],"which":[35,125,179],"is":[36,82,115,134,148],"impractical":[37],"owing":[38],"to":[39,117,129],"varying":[41,172],"working":[42,173],"conditions.":[43],"Furthermore,":[44],"interpretability":[46],"model":[50],"has":[51],"always":[52],"a":[54,59,101],"focus":[55],"attention.":[57],"Therefore,":[58],"novel":[60],"interpretable":[61],"empowered":[62],"transfer":[64,139,183],"framework":[65],"(IEDTF)":[66],"based":[67],"on":[68,150],"contrastive":[70,109],"convolution,":[71],"Wasserstein":[72],"distance":[73],"(WD),":[74],"improved":[76],"Gramian":[77],"angular":[78],"summation":[79],"field":[80],"(IGASF)":[81],"proposed.":[83],"By":[84],"blending":[85],"multichannel":[86],"parallel":[87],"spatial":[89],"polling":[90],"mechanisms,":[91],"proposed":[93,116,135,146],"method":[94,147],"can":[95,166],"adequately":[96],"exploit":[97],"multiscale":[98],"information":[99],"at":[100],"level":[103],"from":[104,122],"source":[106],"domain.":[107],"Then,":[108],"learning":[110],"combined":[111],"with":[112,156],"WD":[114],"establish":[118],"relationships":[119],"data":[121,128],"different":[123,157],"domains,":[124],"generalizes":[126],"labeled":[127],"unlabeled":[130],"data.":[131],"The":[132,142],"IGASF":[133],"for":[136],"interpreting":[137],"distinguishable":[138],"features":[140],"intuitively.":[141],"effectiveness":[143],"demonstrated":[149],"bearing":[154,158,189],"dataset":[155],"positions.":[160],"Experimental":[161],"results":[162],"indicate":[163],"IEDTF":[165],"locate":[167],"positions":[169],"exactly":[170],"under":[171],"conditions":[174],"shows":[176],"high":[177],"stability,":[178],"outperforms":[180],"many":[181],"existing":[182],"models":[184],"applied":[185],"diagnosis.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
