{"id":"https://openalex.org/W7123367758","doi":"https://doi.org/10.1109/tr.2025.3643732","title":"Multisource Deep Adversarial Decoupled Autoencoder Network for State Recognition of High-Speed Train Brake Pads","display_name":"Multisource Deep Adversarial Decoupled Autoencoder Network for State Recognition of High-Speed Train Brake Pads","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7123367758","doi":"https://doi.org/10.1109/tr.2025.3643732"},"language":null,"primary_location":{"id":"doi:10.1109/tr.2025.3643732","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2025.3643732","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/A5122871791","display_name":"Min Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Zhang","raw_affiliation_strings":["School of Mechanical Engineering and Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-0905-9303","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122847917","display_name":"Jiamin Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiamin Li","raw_affiliation_strings":["School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0009-0232-2138","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110483066","display_name":"Zhuang Kang","orcid":"https://orcid.org/0009-0006-6962-0357"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuang Kang","raw_affiliation_strings":["School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0006-6962-0357","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122865396","display_name":"Tong Lan","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Lan","raw_affiliation_strings":["School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0005-3968-3261","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121256312","display_name":"Haohao Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haohao Ding","raw_affiliation_strings":["School of Mechanical Engineering and Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-0094-8646","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":6.3527,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.91396532,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"75","issue":null,"first_page":"639","last_page":"649"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12197","display_name":"Brake Systems and Friction Analysis","score":0.7290999889373779,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T12197","display_name":"Brake Systems and Friction Analysis","score":0.7290999889373779,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.09619999676942825,"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/T10842","display_name":"Railway Engineering and Dynamics","score":0.05849999934434891,"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/autoencoder","display_name":"Autoencoder","score":0.7488999962806702},{"id":"https://openalex.org/keywords/brake","display_name":"Brake","score":0.6118000149726868},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.46070000529289246},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41260001063346863},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40470001101493835},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.3903000056743622},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3815000057220459},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.37860000133514404},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3709000051021576}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7488999962806702},{"id":"https://openalex.org/C2780999251","wikidata":"https://www.wikidata.org/wiki/Q17022503","display_name":"Brake","level":2,"score":0.6118000149726868},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6103000044822693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.519599974155426},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.46070000529289246},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41260001063346863},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40470001101493835},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.3903000056743622},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3709000051021576},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3637000024318695},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.36010000109672546},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.3384999930858612},{"id":"https://openalex.org/C129537906","wikidata":"https://www.wikidata.org/wiki/Q7603913","display_name":"State variable","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.32690000534057617},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C76047896","wikidata":"https://www.wikidata.org/wiki/Q1786258","display_name":"Powertrain","level":3,"score":0.2782000005245209},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.27720001339912415},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.26440000534057617}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tr.2025.3643732","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2025.3643732","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/G1622975448","display_name":null,"funder_award_id":"U22A20181","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3670501642","display_name":null,"funder_award_id":"52305216","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4334731084","display_name":null,"funder_award_id":"52435004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7771099591","display_name":null,"funder_award_id":"2025ZNSFSC0426","funder_id":"https://openalex.org/F4320329861","funder_display_name":"Natural Science Foundation of Sichuan Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329861","display_name":"Natural Science Foundation of Sichuan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2070676419","https://openalex.org/W2969372261","https://openalex.org/W3049397905","https://openalex.org/W3088781898","https://openalex.org/W3106901053","https://openalex.org/W4225090162","https://openalex.org/W4283077815","https://openalex.org/W4285109832","https://openalex.org/W4313186375","https://openalex.org/W4313597532","https://openalex.org/W4390660109","https://openalex.org/W4391795692","https://openalex.org/W4391915398","https://openalex.org/W4393112045","https://openalex.org/W4401122139","https://openalex.org/W4401163949","https://openalex.org/W4401214949","https://openalex.org/W4402297726","https://openalex.org/W4402404500","https://openalex.org/W4403381453","https://openalex.org/W4404687942","https://openalex.org/W4405092770","https://openalex.org/W4405785442","https://openalex.org/W4405785529","https://openalex.org/W4406323296","https://openalex.org/W4406866111","https://openalex.org/W4407081086","https://openalex.org/W4407595936","https://openalex.org/W4407596503","https://openalex.org/W4407616341","https://openalex.org/W4407712966","https://openalex.org/W4407902231","https://openalex.org/W4407949537","https://openalex.org/W4408327531","https://openalex.org/W4408399041","https://openalex.org/W4408556058","https://openalex.org/W4408682791","https://openalex.org/W4409270617","https://openalex.org/W4411127626","https://openalex.org/W4411855435"],"related_works":[],"abstract_inverted_index":{"High-speed":[0],"train":[1],"brake":[2,32,54],"pads":[3],"state":[4,34,56,72],"recognition":[5],"faces":[6],"the":[7,31,70,75,105,115,128,133,153,171,188,197],"problems":[8],"of":[9,53,57,74,84,108,118,165,178],"single":[10],"data":[11,28],"source":[12],"feature":[13],"characterization":[14,67],"limitation":[15],"and":[16,93,110,123,184,191],"significant":[17],"domain":[18,124,200],"shifts":[19],"under":[20,60],"variable":[21,61],"working":[22,62],"conditions.":[23,63,161],"Considering":[24],"that":[25,170],"multi-source":[26,43,85,144],"heterogeneous":[27,86],"can":[29],"characterize":[30],"pad":[33,55],"from":[35],"different":[36],"physical":[37],"dimensions,":[38],"this":[39],"paper":[40],"proposes":[41],"a":[42,65,96,136],"deep":[44,97],"adversarial":[45,98],"decoupled":[46,99],"autoencoder":[47,100],"network":[48],"(MS-DADA)":[49],"for":[50,157],"online":[51],"identification":[52],"high-speed":[58],"trains":[59],"First,":[64],"signal":[66],"system":[68],"covering":[69],"multidimensional":[71],"characteristics":[73],"friction":[76,89],"interface":[77],"is":[78,101,139,181],"constructed":[79],"by":[80,113],"fusing":[81],"three":[82],"kinds":[83],"data,":[87],"including":[88],"coefficient,":[90],"tangential":[91],"acceleration":[92],"noise.":[94],"Second,":[95],"designed":[102],"to":[103,141,193],"realize":[104],"explicit":[106],"decoupling":[107],"domain-invariant":[109],"domain-specific":[111],"features":[112],"utilizing":[114],"synergistic":[116],"mechanism":[117],"mutual":[119],"information":[120],"minimization":[121],"constraint":[122],"adversarial.":[125],"Finally,":[126],"with":[127],"validation":[129],"set":[130],"accuracy":[131,177],"as":[132],"optimization":[134],"objective,":[135],"genetic":[137],"algorithm":[138],"introduced":[140],"dynamically":[142],"allocate":[143],"weights.":[145],"This":[146],"adaptive":[147],"weighted":[148],"fusion":[149],"strategy":[150],"significantly":[151],"enhances":[152],"model's":[154],"generalization":[155,201],"capability":[156],"unknown":[158],"rotational":[159],"speed":[160],"The":[162],"experimental":[163],"results":[164],"10":[166],"cross-speed":[167],"tasks":[168],"show":[169],"proposed":[172],"model":[173],"achieves":[174],"an":[175],"average":[176],"99.12%.":[179],"It":[180],"7.1%,":[182],"9.36%":[183],"26.5%":[185],"higher":[186],"than":[187,196],"single-source":[189],"model,":[190],"3.58%":[192],"6.36%":[194],"better":[195],"current":[198],"leading":[199],"methods.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2026-01-14T00:00:00"}
