{"id":"https://openalex.org/W4379927967","doi":"https://doi.org/10.1109/tim.2023.3284131","title":"A Novel Domain Adaptive Fault Diagnosis Method for Bearings Based on Unbalance Data Generation","display_name":"A Novel Domain Adaptive Fault Diagnosis Method for Bearings Based on Unbalance Data Generation","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4379927967","doi":"https://doi.org/10.1109/tim.2023.3284131"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3284131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3284131","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/A5011132626","display_name":"Baokun Han","orcid":"https://orcid.org/0000-0001-7367-6253"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Baokun Han","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043088278","display_name":"Xingwang Jiang","orcid":"https://orcid.org/0000-0002-8378-823X"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingwang Jiang","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027947686","display_name":"Jinrui Wang","orcid":"https://orcid.org/0000-0001-8690-0672"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinrui Wang","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069886339","display_name":"Zongzhen Zhang","orcid":"https://orcid.org/0000-0002-2022-2116"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongzhen Zhang","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011132626"],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":null,"apc_paid":null,"fwci":5.4859,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.96459435,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9980999827384949,"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":0.9980999827384949,"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/T13891","display_name":"Engineering Diagnostics and Reliability","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T14368","display_name":"Evaluation and Optimization Models","score":0.977400004863739,"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/overfitting","display_name":"Overfitting","score":0.8542947173118591},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6640583872795105},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5916831493377686},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.5288406610488892},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5267635583877563},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5134481191635132},{"id":"https://openalex.org/keywords/undersampling","display_name":"Undersampling","score":0.5133149027824402},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4673246443271637},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4233441948890686},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.387807160615921},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3229954242706299},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2213951051235199}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8542947173118591},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6640583872795105},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5916831493377686},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.5288406610488892},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5267635583877563},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5134481191635132},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.5133149027824402},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4673246443271637},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4233441948890686},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.387807160615921},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3229954242706299},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2213951051235199},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2023.3284131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3284131","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":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.8299999833106995}],"awards":[{"id":"https://openalex.org/G1761188003","display_name":null,"funder_award_id":"ZR2020QE157","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3430244997","display_name":null,"funder_award_id":"ZR2021QE024","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5385151697","display_name":null,"funder_award_id":"ZR2022ME119","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":34,"referenced_works":["https://openalex.org/W1565176583","https://openalex.org/W1582713201","https://openalex.org/W2072857564","https://openalex.org/W2096943734","https://openalex.org/W2115403315","https://openalex.org/W2187089797","https://openalex.org/W2395579298","https://openalex.org/W2765811365","https://openalex.org/W2805975258","https://openalex.org/W2905230381","https://openalex.org/W2908062660","https://openalex.org/W2919115771","https://openalex.org/W2939535241","https://openalex.org/W2946159658","https://openalex.org/W2964201867","https://openalex.org/W2995758361","https://openalex.org/W3092609815","https://openalex.org/W3188809990","https://openalex.org/W3201753566","https://openalex.org/W3214433557","https://openalex.org/W4226343678","https://openalex.org/W4236137412","https://openalex.org/W4240206582","https://openalex.org/W4255421341","https://openalex.org/W4285241854","https://openalex.org/W4285245107","https://openalex.org/W4312537998","https://openalex.org/W4313839141","https://openalex.org/W4319992826","https://openalex.org/W4321016476","https://openalex.org/W4321380810","https://openalex.org/W4324290422","https://openalex.org/W6688325169","https://openalex.org/W6732249622"],"related_works":["https://openalex.org/W2109073422","https://openalex.org/W2887783772","https://openalex.org/W2101754595","https://openalex.org/W2534887053","https://openalex.org/W4320063365","https://openalex.org/W2575656761","https://openalex.org/W2065631063","https://openalex.org/W2378667342","https://openalex.org/W2594567802","https://openalex.org/W2363739414"],"abstract_inverted_index":{"Domain":[0],"adaptive":[1,58,179,183],"fault":[2,63,80,127,145],"diagnosis":[3,64,255],"methods":[4,40,225],"of":[5,20,77,129,143,169,198,217,243,257,277],"bearing":[6,62,79,110,258],"have":[7],"made":[8],"extraordinary":[9],"achievements":[10],"in":[11,34,70,140,226],"recent":[12],"years.":[13],"Among":[14],"these":[15],"methods,":[16],"the":[17,74,84,100,106,113,126,130,144,153,166,170,196,199,208,214,218,222,229,248,254,264,268,281],"vast":[18],"majority":[19],"machine":[21],"learning":[22],"problems":[23,30],"are":[24,31,41,89,122,192],"balanced":[25,96],"classification":[26],"problems.":[27,48],"However,":[28],"imbalance":[29,47],"very":[32],"common":[33],"practical":[35],"applications.":[36],"Undersampling":[37],"and":[38,83,86,99,108,132,135,172,236,259],"oversampling":[39],"often":[42],"used":[43,123],"to":[44,93,124,148,164,194],"deal":[45],"with":[46,105,221,280],"Inspired":[49],"by":[50,157,274],"Wasserstein":[51],"generative":[52],"adversarial":[53],"network":[54,147],"(WGAN),":[55],"a":[56,95,176],"domain":[57,115,154,178],"guided":[59,156],"WGAN":[60,92],"for":[61,187],"under":[65],"imbalanced":[66,188],"samples":[67],"is":[68,81,103,138,162,185,232,271],"proposed":[69,186,200],"this":[71,227],"article.":[72],"First,":[73],"unbalanced":[75],"data":[76,85,97,102],"each":[78,141],"collected,":[82],"random":[87],"noise":[88],"generated":[90,109],"through":[91,112],"generate":[94],"set,":[98],"processed":[101],"compared":[104,220,279],"real":[107],"signals":[111],"frequency":[114],"feature":[116,167],"distribution.":[117],"Then,":[118],"stacked":[119],"autoencoders":[120],"(SAEs)":[121],"extract":[125],"features":[128],"target":[131,171],"source":[133,173],"domains":[134],"L2":[136],"regularization":[137],"added":[139],"layer":[142],"extractor":[146],"prevent":[149],"model":[150],"overfitting.":[151],"Finally,":[152],"adaptation":[155],"maximum":[158],"mean":[159],"discrepancy":[160],"(MMD)":[161],"employed":[163],"complete":[165],"alignment":[168],"domains.":[174],"Therefore,":[175],"novel":[177],"method":[180,210,250],"named":[181],"WGAN-domain":[182],"(DAWGAN)":[184],"samples.":[189],"Two":[190],"experiments":[191,245],"applied":[193],"verify":[195],"superiority":[197],"DAWGAN":[201,209,249],"method.":[202,283],"The":[203],"experimental":[204],"results":[205,242],"show":[206,246],"that":[207,247],"can":[211,251],"significantly":[212,252],"improve":[213,253],"diagnostic":[215],"accuracy":[216,256],"bearing,":[219],"five":[223],"comparison":[224,282],"article,":[228],"average":[230,276],"increase":[231],"more":[233],"than":[234,263],"10%,":[235],"it":[237],"has":[238,260],"better":[239,261],"stability.":[240],"Comparison":[241],"two":[244],"stability":[262],"other":[265],"methods.":[266],"Meanwhile,":[267],"calculation":[269],"time":[270],"also":[272],"shortened":[273],"an":[275],"40%":[278]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":10}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}