{"id":"https://openalex.org/W4200450554","doi":"https://doi.org/10.1108/ijicc-08-2021-0153","title":"The multilabel fault diagnosis model of bearing based on integrated convolutional neural network and gated recurrent unit","display_name":"The multilabel fault diagnosis model of bearing based on integrated convolutional neural network and gated recurrent unit","publication_year":2021,"publication_date":"2021-12-20","ids":{"openalex":"https://openalex.org/W4200450554","doi":"https://doi.org/10.1108/ijicc-08-2021-0153"},"language":"en","primary_location":{"id":"doi:10.1108/ijicc-08-2021-0153","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijicc-08-2021-0153","pdf_url":null,"source":{"id":"https://openalex.org/S124503262","display_name":"International Journal of Intelligent Computing and Cybernetics","issn_l":"1756-378X","issn":["1756-378X","1756-3798"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Computing and Cybernetics","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/A5090742727","display_name":"Shanling Han","orcid":"https://orcid.org/0000-0001-8108-6843"},"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":"Shanling Han","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0001-8108-6843","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/A5073292113","display_name":"Shoudong Zhang","orcid":"https://orcid.org/0000-0001-7332-7627"},"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":"Shoudong Zhang","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China"],"raw_orcid":null,"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/A5100339558","display_name":"Yong Li","orcid":"https://orcid.org/0000-0001-7228-7790"},"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":"Yong Li","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0001-7228-7790","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/A5100336427","display_name":"Long Chen","orcid":"https://orcid.org/0000-0003-0184-5446"},"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":"Long Chen","raw_affiliation_strings":["College of Materials Science and Engineering, Shandong University of Science and Technology, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Materials Science and Engineering, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":null,"apc_paid":null,"fwci":1.7594,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.84975733,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"15","issue":"3","first_page":"401","last_page":"413"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9969000220298767,"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":0.9969000220298767,"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/T12086","display_name":"Structural Integrity and Reliability Analysis","score":0.9603000283241272,"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/T13891","display_name":"Engineering Diagnostics and Reliability","score":0.9448000192642212,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8011337518692017},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7420100569725037},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6813860535621643},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6361432075500488},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.6178058385848999},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5380468368530273},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.501326322555542},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4644045829772949},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4263290762901306},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4256318211555481},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.41637712717056274},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3962436020374298},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3308393061161041},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.1543218195438385}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8011337518692017},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7420100569725037},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6813860535621643},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6361432075500488},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.6178058385848999},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5380468368530273},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.501326322555542},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4644045829772949},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4263290762901306},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4256318211555481},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.41637712717056274},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3962436020374298},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3308393061161041},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.1543218195438385},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/ijicc-08-2021-0153","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijicc-08-2021-0153","pdf_url":null,"source":{"id":"https://openalex.org/S124503262","display_name":"International Journal of Intelligent Computing and Cybernetics","issn_l":"1756-378X","issn":["1756-378X","1756-3798"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Computing and Cybernetics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2114315281","https://openalex.org/W2157331557","https://openalex.org/W2504909090","https://openalex.org/W2530133016","https://openalex.org/W2584391867","https://openalex.org/W2744790985","https://openalex.org/W2908271077","https://openalex.org/W2912412749","https://openalex.org/W2915273349","https://openalex.org/W2968098319","https://openalex.org/W2971479067","https://openalex.org/W2995439439","https://openalex.org/W3020024605","https://openalex.org/W3021261417","https://openalex.org/W3035900022","https://openalex.org/W3037911243","https://openalex.org/W3038033099","https://openalex.org/W3091977516","https://openalex.org/W3092592567","https://openalex.org/W3112055983","https://openalex.org/W3118616132","https://openalex.org/W3129587046","https://openalex.org/W3130900996","https://openalex.org/W3134236859","https://openalex.org/W3158381863","https://openalex.org/W3173296402","https://openalex.org/W3177031970","https://openalex.org/W3177553803"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2035937180","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W3202613528"],"abstract_inverted_index":{"Purpose":[0],"Intelligent":[1],"diagnosis":[2,25,188],"of":[3,19,26,29,40,73,99,159,189,216,254,268],"equipment":[4,13],"faults":[5,14,208],"can":[6,42,205],"effectively":[7],"avoid":[8],"the":[9,17,20,24,35,55,59,78,97,106,111,128,132,140,144,157,160,167,176,192,199,203,223,227,230,234,239,259,264,276],"shutdown":[10],"caused":[11],"by":[12,46,104,258],"and":[15,38,49,52,70,116,143,175,184,191,233,237,263],"improve":[16,77],"safety":[18],"equipment.":[21],"At":[22],"present,":[23],"various":[27],"kinds":[28],"bearing":[30,90,101,151,218],"fault":[31,68,74,83,91,187,214,228,256,270,283],"information,":[32],"such":[33],"as":[34],"occurrence,":[36],"location":[37],"degree":[39],"fault,":[41],"be":[43],"carried":[44],"out":[45],"machine":[47],"learning":[48,51],"deep":[50],"realized":[53],"through":[54],"multiclassification":[56,60,200],"method.":[57,109,201],"However,":[58],"method":[61,195],"is":[62,87,121,153,173,179,196,242,247,272],"not":[63],"perfect":[64],"in":[65,170,186,275],"distinguishing":[66],"similar":[67],"categories":[69],"visual":[71],"representation":[72],"information.":[75],"To":[76],"above":[79],"shortcomings,":[80],"an":[81],"end-to-end":[82],"multilabel":[84,193,245],"classification":[85,194,252],"model":[86,204],"proposed":[88,177],"for":[89],"diagnosis.":[92],"Design/methodology/approach":[93],"In":[94],"this":[95],"model,":[96],"labels":[98,215],"each":[100,217,255,269],"are":[102,219],"binarized":[103],"using":[105],"binary":[107,240,251,260],"relevance":[108,261],"Then,":[110],"integrated":[112],"convolutional":[113,141],"neural":[114],"network":[115,134,178],"gated":[117],"recurrent":[118],"unit":[119],"(CNN-GRU)":[120],"employed":[122],"to":[123,155,198,222],"classify":[124,207],"faults.":[125],"Different":[126],"from":[127],"general":[129],"CNN":[130,185],"networks,":[131],"CNN-GRU":[133],"adds":[135],"multiple":[136],"GRU":[137],"layers":[138,142],"after":[139],"pool":[145],"layers.":[146],"Findings":[147],"The":[148,162,213,244],"Paderborn":[149],"University":[150],"dataset":[152],"utilized":[154],"demonstrate":[156],"practicability":[158],"model.":[161],"experimental":[163],"results":[164],"show":[165],"that":[166],"average":[168],"accuracy":[169],"test":[171],"set":[172],"99.7%,":[174],"better":[180],"than":[181],"multilayer":[182],"perceptron":[183],"bearing,":[190],"superior":[197],"Consequently,":[202],"intuitively":[206],"with":[209],"higher":[210],"accuracy.":[211],"Originality/value":[212],"labeled":[220],"according":[221],"failure":[224],"or":[225],"not,":[226],"location,":[229],"damage":[231,235],"mode":[232],"degree,":[236],"then":[238],"value":[241,267],"obtained.":[243],"problem":[246,253],"transformed":[248],"into":[249],"a":[250],"label":[257,271],"method,":[262],"predicted":[265],"probability":[266],"directly":[273],"output":[274,277],"layer,":[278],"which":[279],"visually":[280],"distinguishes":[281],"different":[282],"conditions.":[284]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}