{"id":"https://openalex.org/W3081032406","doi":"https://doi.org/10.1109/tim.2020.3017900","title":"Multitask Learning Based on Lightweight 1DCNN for Fault Diagnosis of Wheelset Bearings","display_name":"Multitask Learning Based on Lightweight 1DCNN for Fault Diagnosis of Wheelset Bearings","publication_year":2020,"publication_date":"2020-08-26","ids":{"openalex":"https://openalex.org/W3081032406","doi":"https://doi.org/10.1109/tim.2020.3017900","mag":"3081032406"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2020.3017900","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3017900","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/A5003564537","display_name":"Zhiliang Liu","orcid":"https://orcid.org/0000-0002-4133-8230"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiliang Liu","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100751566","display_name":"Huan Wang","orcid":"https://orcid.org/0000-0002-1403-5314"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huan Wang","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396430","display_name":"Junjie Liu","orcid":"https://orcid.org/0000-0002-5100-5253"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Liu","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088716214","display_name":"Yong Qin","orcid":"https://orcid.org/0000-0002-6519-8316"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Qin","raw_affiliation_strings":["State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008028075","display_name":"Dandan Peng","orcid":"https://orcid.org/0000-0003-0890-9254"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Dandan Peng","raw_affiliation_strings":["KU Leuven, Leuven, Belgium"],"affiliations":[{"raw_affiliation_string":"KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5003564537"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":10.9814,"has_fulltext":false,"cited_by_count":134,"citation_normalized_percentile":{"value":0.98940347,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"70","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":0.9980000257492065,"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":0.9980000257492065,"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":0.989799976348877,"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"}},{"id":"https://openalex.org/T10809","display_name":"Occupational Health and Safety Research","score":0.9077000021934509,"subfield":{"id":"https://openalex.org/subfields/3614","display_name":"Radiological and Ultrasound Technology"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.7552225589752197},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.724158525466919},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7148460149765015},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.629871129989624},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.595421314239502},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5623579025268555},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5500895977020264},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5097441077232361},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4877229630947113},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4865800142288208},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48061317205429077},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45256713032722473},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3299270272254944},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2505578398704529}],"concepts":[{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.7552225589752197},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.724158525466919},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7148460149765015},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.629871129989624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.595421314239502},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5623579025268555},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5500895977020264},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5097441077232361},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4877229630947113},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4865800142288208},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48061317205429077},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45256713032722473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3299270272254944},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2505578398704529},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2020.3017900","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3017900","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":[],"awards":[{"id":"https://openalex.org/G4769290947","display_name":null,"funder_award_id":"61833002","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1799366690","https://openalex.org/W1982878030","https://openalex.org/W1985716425","https://openalex.org/W2081910282","https://openalex.org/W2102969258","https://openalex.org/W2187089797","https://openalex.org/W2277064738","https://openalex.org/W2337287714","https://openalex.org/W2471080557","https://openalex.org/W2485614840","https://openalex.org/W2509453848","https://openalex.org/W2514728168","https://openalex.org/W2523408358","https://openalex.org/W2583612411","https://openalex.org/W2584994008","https://openalex.org/W2592772746","https://openalex.org/W2595657631","https://openalex.org/W2605606145","https://openalex.org/W2624871570","https://openalex.org/W2753709519","https://openalex.org/W2765284480","https://openalex.org/W2768753204","https://openalex.org/W2779615422","https://openalex.org/W2810057162","https://openalex.org/W2885948040","https://openalex.org/W2892075914","https://openalex.org/W2895763863","https://openalex.org/W2905949437","https://openalex.org/W2906578288","https://openalex.org/W2913340405","https://openalex.org/W2915229515","https://openalex.org/W2919115771","https://openalex.org/W2922246408","https://openalex.org/W2922660557","https://openalex.org/W2933532955","https://openalex.org/W2943909972","https://openalex.org/W2973424371","https://openalex.org/W2975932043","https://openalex.org/W2989818023","https://openalex.org/W2991661665","https://openalex.org/W3000384844","https://openalex.org/W3030997042","https://openalex.org/W6739365718"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2947043951","https://openalex.org/W4399188509","https://openalex.org/W4312417841"],"abstract_inverted_index":{"In":[0,107],"recent":[1],"years,":[2],"deep":[3],"learning":[4,138],"has":[5,166],"been":[6],"proved":[7],"to":[8,68,90,119,154],"be":[9],"a":[10,77,167],"promising":[11],"bearing":[12,131],"fault":[13,157],"diagnosis":[14,28,158],"technology.":[15],"However,":[16],"most":[17],"of":[18,53,72,123,143,160],"the":[19,51,70,73,85,110,121,124,136,144,149,152,156,161,164],"existing":[20],"methods":[21],"are":[22],"based":[23],"on":[24],"single-task":[25],"learning.":[26],"Fault":[27],"task":[29,57,62,97],"(FDT)":[30],"is":[31,45],"treated":[32],"as":[33,64],"an":[34],"independent":[35],"task,":[36],"and":[37,59,75,98,151,163],"rich":[38],"correlation":[39],"information":[40,146],"contained":[41],"in":[42,174],"different":[43,101],"tasks":[44,67,102,118],"ignored.":[46],"Therefore,":[47],"this":[48,108],"article":[49],"explores":[50],"possibility":[52],"using":[54],"speed":[55],"identification":[56,61],"(SIT)":[58],"load":[60],"(LIT)":[63],"two":[65],"auxiliary":[66],"improve":[69,120,155],"performance":[71,122,159,169],"FDT":[74],"proposes":[76],"multitask":[78,137],"one-dimensional":[79],"convolutional":[80],"neural":[81],"network":[82,89],"(MT-1DCNN).":[83],"Specifically,":[84],"MT-1DCNN":[86,111,165],"utilizes":[87],"trunk":[88],"learn":[91],"shared":[92],"features":[93,114],"required":[94],"for":[95],"every":[96],"then":[99],"processes":[100],"through":[103],"multiple":[104],"task-specific":[105],"branches.":[106],"way,":[109],"can":[112,139],"utilize":[113],"learned":[115],"by":[116,148],"related":[117],"FDT.":[125],"The":[126],"experimental":[127],"results":[128],"with":[129],"wheelset":[130],"data":[132],"set":[133],"show":[134],"that":[135],"make":[140],"full":[141],"use":[142],"feature":[145],"captured":[147],"SIT":[150],"LIT":[153],"network,":[162],"better":[168],"than":[170],"five":[171],"excellent":[172],"networks":[173],"accuracy.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":32},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
