{"id":"https://openalex.org/W7160525027","doi":"https://doi.org/10.1109/tr.2026.3691333","title":"Targeted Augmentation Domain-Mixed Network for Single-Source Domain Generalization Fault Diagnosis","display_name":"Targeted Augmentation Domain-Mixed Network for Single-Source Domain Generalization Fault Diagnosis","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7160525027","doi":"https://doi.org/10.1109/tr.2026.3691333"},"language":null,"primary_location":{"id":"doi:10.1109/tr.2026.3691333","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2026.3691333","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/A5135601206","display_name":"He Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Ren","raw_affiliation_strings":["School of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9710-7805","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou, China","institution_ids":["https://openalex.org/I4210153482"]}]},{"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/A5135627242","display_name":"Zhongkui Zhu","orcid":null},"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"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135576967","display_name":"Yi Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhang","raw_affiliation_strings":["School of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6857-3217","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou, China","institution_ids":["https://openalex.org/I4210153482"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135601995","display_name":"Song Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Zhang","raw_affiliation_strings":["Changzhou NRB Corporation, Changzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-0597-5973","affiliations":[{"raw_affiliation_string":"Changzhou NRB Corporation, Changzhou, China","institution_ids":["https://openalex.org/I4210153482"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.52479994,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"75","issue":null,"first_page":"1925","last_page":"1938"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9625999927520752,"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":0.9625999927520752,"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":0.0071000000461936,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.004600000102072954,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.8241999745368958},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6535999774932861},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6212999820709229},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5565999746322632},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5101000070571899},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4690000116825104},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4097000062465668},{"id":"https://openalex.org/keywords/mixing","display_name":"Mixing (physics)","score":0.4032000005245209},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.37450000643730164}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.8241999745368958},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6535999774932861},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6327000260353088},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6212999820709229},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5565999746322632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.511900007724762},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5101000070571899},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4690000116825104},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4097000062465668},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.4032000005245209},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3783000111579895},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.37450000643730164},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3377000093460083},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3325999975204468},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3158000111579895},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.30390000343322754},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2978000044822693},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.2596000134944916},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.25220000743865967},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tr.2026.3691333","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2026.3691333","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":[],"awards":[{"id":"https://openalex.org/G5065864682","display_name":null,"funder_award_id":"52275157","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"},{"id":"https://openalex.org/G7496859879","display_name":null,"funder_award_id":"BK20250970","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Machinery":[0],"typically":[1],"operates":[2],"under":[3],"constantly":[4],"changing":[5],"working":[6,27,33,190],"conditions":[7,191],"in":[8,77,97,173],"real-time":[9],"production.":[10],"Directly":[11],"applying":[12],"a":[13,25,30,36,69,90,109,122,131],"diagnostic":[14],"model,":[15],"which":[16,94],"has":[17],"been":[18],"trained":[19],"solely":[20],"on":[21,194],"monitoring":[22],"data":[23],"from":[24,104,149],"single":[26],"condition,":[28],"to":[29,51,58,129,188],"new":[31,132],"unseen":[32,189],"condition":[34],"poses":[35],"notably":[37],"challenging":[38],"task":[39],"called":[40],"single-source":[41],"domain":[42,100,123,134],"generalization":[43,182],"(SSDG)":[44],"fault":[45,82],"diagnosis.":[46],"Current":[47],"research":[48],"mainly":[49],"aims":[50],"augment":[52],"source-domain":[53,106],"training":[54],"samples":[55,96,107,148,172],"but":[56],"struggles":[57],"maintain":[59],"health":[60],"state":[61,119],"information":[62],"invariance":[63],"for":[64,80,155],"diverse":[65,136],"augmented":[66,99,153,171],"samples.":[67,159],"Therefore,":[68],"targeted":[70,91],"augmentation":[71,92,157],"domain-mixed":[72],"network":[73],"(TADNet)":[74],"is":[75,127,192],"proposed":[76,186],"this":[78],"paper":[79],"SSDG":[81],"diagnosis":[83,181],"of":[84,118,146,158,170,176,184],"rotating":[85,196],"machinery.":[86],"The":[87,160,179],"TADNet":[88,161],"constructs":[89],"chain,":[93],"generates":[95],"an":[98],"with":[101,135],"different":[102],"distributions":[103],"the":[105,115,143,147,150,164,174,185],"through":[108,138],"chained":[110],"generation":[111],"structure,":[112],"and":[113,140,152,167],"ensures":[114],"semantic":[116,168],"consistency":[117,169],"features.":[120],"Additionally,":[121],"random":[124],"mixing":[125,142],"strategy":[126],"established":[128],"synthesize":[130],"mixed":[133],"distributions,":[137],"probabilistically":[139],"randomly":[141],"feature":[144],"statistics":[145],"source":[151],"domains,":[154],"further":[156],"effectively":[162],"balances":[163],"distribution":[165],"diversity":[166],"course":[175],"model":[177],"training.":[178],"superior":[180],"ability":[183],"method":[187],"demonstrated":[193],"two":[195],"machinery":[197],"datasets.":[198]},"counts_by_year":[],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2026-05-08T00:00:00"}
