{"id":"https://openalex.org/W4388407747","doi":"https://doi.org/10.1109/tim.2023.3330218","title":"Classifier Discrepancy Guided Soft-Weight Adaptation Network for Machinery Fault Diagnosis Under Domain and Category Shift","display_name":"Classifier Discrepancy Guided Soft-Weight Adaptation Network for Machinery Fault Diagnosis Under Domain and Category Shift","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388407747","doi":"https://doi.org/10.1109/tim.2023.3330218"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3330218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3330218","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/A5100431162","display_name":"Rui Wang","orcid":"https://orcid.org/0000-0001-8960-596X"},"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":true,"raw_author_name":"Rui Wang","raw_affiliation_strings":["School of Rail Transportation, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-8960-596X","affiliations":[{"raw_affiliation_string":"School of Rail Transportation, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072145928","display_name":"Weiguo Huang","orcid":"https://orcid.org/0000-0002-6734-2019"},"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":"Weiguo Huang","raw_affiliation_strings":["School of Rail Transportation, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6734-2019","affiliations":[{"raw_affiliation_string":"School of Rail Transportation, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054789987","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-3392-1020"},"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":"Jun Wang","raw_affiliation_strings":["School of Rail Transportation, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3392-1020","affiliations":[{"raw_affiliation_string":"School of Rail Transportation, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015527442","display_name":"Chuancang Ding","orcid":"https://orcid.org/0000-0002-7610-5293"},"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":"Chuancang Ding","raw_affiliation_strings":["School of Rail Transportation, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7610-5293","affiliations":[{"raw_affiliation_string":"School of Rail Transportation, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091072755","display_name":"Changqing Shen","orcid":"https://orcid.org/0000-0002-5143-8366"},"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":"Changqing Shen","raw_affiliation_strings":["School of Rail Transportation, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5143-8366","affiliations":[{"raw_affiliation_string":"School of Rail Transportation, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100758788","display_name":"Zhongkui Zhu","orcid":"https://orcid.org/0000-0001-9827-4154"},"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":"Zhongkui Zhu","raw_affiliation_strings":["School of Rail Transportation, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9827-4154","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":6,"corresponding_author_ids":["https://openalex.org/A5100431162"],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":2.1521,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.87639527,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9894999861717224,"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":0.9894999861717224,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9864000082015991,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9749000072479248,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.764499843120575},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7369862794876099},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6565430164337158},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6250448226928711},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6128202676773071},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5383762717247009},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46033889055252075},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4539220333099365},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4460349380970001},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3642747700214386}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.764499843120575},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7369862794876099},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6565430164337158},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6250448226928711},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6128202676773071},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5383762717247009},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46033889055252075},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4539220333099365},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4460349380970001},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3642747700214386},{"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/tim.2023.3330218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3330218","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/10","score":0.7400000095367432,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3234005388","display_name":null,"funder_award_id":"52075353","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3401778377","display_name":null,"funder_award_id":"52205119","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7412655461","display_name":null,"funder_award_id":"52275121","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":35,"referenced_works":["https://openalex.org/W2612554669","https://openalex.org/W2779610669","https://openalex.org/W2798593490","https://openalex.org/W2903917280","https://openalex.org/W2948069880","https://openalex.org/W2962687275","https://openalex.org/W2964109570","https://openalex.org/W2975932043","https://openalex.org/W2991632793","https://openalex.org/W2998115938","https://openalex.org/W2999414995","https://openalex.org/W3036403470","https://openalex.org/W3040865353","https://openalex.org/W3110199296","https://openalex.org/W3110510730","https://openalex.org/W3111706174","https://openalex.org/W3122985179","https://openalex.org/W3142041738","https://openalex.org/W3159025054","https://openalex.org/W3201753566","https://openalex.org/W3209651137","https://openalex.org/W4206057957","https://openalex.org/W4210685411","https://openalex.org/W4223996660","https://openalex.org/W4225605564","https://openalex.org/W4225709684","https://openalex.org/W4226067624","https://openalex.org/W4285213432","https://openalex.org/W4285237966","https://openalex.org/W4292387424","https://openalex.org/W4312730910","https://openalex.org/W4380451824","https://openalex.org/W4382045866","https://openalex.org/W4382405162","https://openalex.org/W6683633756"],"related_works":["https://openalex.org/W1487808658","https://openalex.org/W3080655457","https://openalex.org/W4318818647","https://openalex.org/W2145868540","https://openalex.org/W3166286441","https://openalex.org/W3214142563","https://openalex.org/W3136267388","https://openalex.org/W4287263085","https://openalex.org/W3186065094","https://openalex.org/W3204418343"],"abstract_inverted_index":{"Cross-domain":[0],"diagnosis":[1,18,63,187],"approaches":[2],"based":[3],"on":[4,102,168],"transfer":[5],"learning":[6,101],"have":[7,52],"received":[8],"considerable":[9],"attention":[10],"in":[11,45,56,189],"the":[12,21,38,61,114,117,120,131,154,178,190],"past":[13],"few":[14],"years.":[15],"Conventional":[16],"closed-set":[17,39],"tasks,":[19],"where":[20],"fault":[22,54,62,186],"modes":[23,55],"of":[24,116,119,133,192],"source":[25],"and":[26,108,157,194],"target":[27,103,134],"machines":[28,50],"are":[29,31],"consistent,":[30],"effectively":[32,105],"addressed":[33],"by":[34],"existing":[35],"methods.":[36],"However,":[37],"assumption":[40],"is":[41,96,141,150],"difficult":[42],"to":[43,85,98,137,152,158],"hold":[44],"actual":[46],"applications":[47],"because":[48],"different":[49,53,82,91],"usually":[51],"real":[57,170],"industries.":[58],"To":[59],"handle":[60],"problem":[64],"with":[65,172],"category":[66,195],"shift,":[67],"this":[68],"study":[69],"proposes":[70],"a":[71,123,145,182],"novel":[72],"classifier":[73,95,147],"discrepancy-guided":[74],"soft-weight":[75,125],"adaptation":[76],"network.":[77],"The":[78,164],"network":[79,180],"incorporates":[80],"two":[81,169],"state":[83],"classifiers":[84],"extract":[86],"domain-invariant":[87],"discriminative":[88],"features":[89],"from":[90],"domains.":[92,112,163],"An":[93],"outlier":[94],"constructed":[97],"perform":[99],"pseudo-label":[100],"samples,":[104],"separating":[106],"shared-class":[107],"unknown-class":[109],"samples":[110,135],"between":[111],"On":[113],"basis":[115],"entropy":[118],"class":[121],"likelihood,":[122],"sample-wise":[124],"term,":[126],"which":[127],"can":[128],"adaptatively":[129],"measure":[130],"similarity":[132],"attributed":[136],"shared":[138],"label":[139],"space,":[140],"constructed.":[142],"After":[143],"that,":[144],"weighted":[146],"discrepancy":[148],"loss":[149],"designed":[151],"bridge":[153],"domain":[155,193],"shift":[156],"achieve":[159],"known-class":[160],"alignment":[161],"across":[162],"experimental":[165],"results":[166],"conducted":[167],"datasets":[171],"diverse":[173],"diagnostic":[174],"tasks":[175],"demonstrate":[176],"that":[177],"proposed":[179],"offers":[181],"promising":[183],"solution":[184],"for":[185],"problems":[188],"presence":[191],"shift.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}