{"id":"https://openalex.org/W4397012675","doi":"https://doi.org/10.1017/s0890060423000197","title":"A novel intelligent fault diagnosis method of bearing based on multi-head self-attention convolutional neural network","display_name":"A novel intelligent fault diagnosis method of bearing based on multi-head self-attention convolutional neural network","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4397012675","doi":"https://doi.org/10.1017/s0890060423000197"},"language":"en","primary_location":{"id":"doi:10.1017/s0890060423000197","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s0890060423000197","pdf_url":null,"source":{"id":"https://openalex.org/S4210193102","display_name":"Artificial intelligence for engineering design analysis and manufacturing","issn_l":"0890-0604","issn":["0890-0604","1469-1760"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence for Engineering Design, Analysis and Manufacturing","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/A5065751919","display_name":"Hang Ren","orcid":"https://orcid.org/0009-0001-7532-059X"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Ren","raw_affiliation_strings":["College of Mechatronic Engineering, Harbin Engineering University, Harbin\u00a0150001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechatronic Engineering, Harbin Engineering University, Harbin\u00a0150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035319037","display_name":"Shaogang Liu","orcid":"https://orcid.org/0000-0002-5764-8698"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaogang Liu","raw_affiliation_strings":["College of Mechatronic Engineering, Harbin Engineering University, Harbin\u00a0150001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechatronic Engineering, Harbin Engineering University, Harbin\u00a0150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067314253","display_name":"Bo Qiu","orcid":"https://orcid.org/0000-0002-0191-3413"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bo Qiu","raw_affiliation_strings":["CSSC Fire Equipment Co., Ltd, Jiangxi\u00a0332000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CSSC Fire Equipment Co., Ltd, Jiangxi\u00a0332000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113746166","display_name":"Hong Guo","orcid":"https://orcid.org/0000-0002-2719-9465"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Guo","raw_affiliation_strings":["College of Mechatronic Engineering, Harbin Engineering University, Harbin\u00a0150001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechatronic Engineering, Harbin Engineering University, Harbin\u00a0150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043140224","display_name":"Dan Zhao","orcid":"https://orcid.org/0000-0001-5639-2056"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dan Zhao","raw_affiliation_strings":["College of Mechatronic Engineering, Harbin Engineering University, Harbin\u00a0150001, China"],"raw_orcid":"https://orcid.org/0000-0001-5639-2056","affiliations":[{"raw_affiliation_string":"College of Mechatronic Engineering, Harbin Engineering University, Harbin\u00a0150001, China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5043140224"],"corresponding_institution_ids":["https://openalex.org/I151727225"],"apc_list":null,"apc_paid":null,"fwci":2.8397,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.9060187,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"38","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9990000128746033,"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":0.9990000128746033,"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":0.9952999949455261,"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":0.9872999787330627,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.817233145236969},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6952564120292664},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6228971481323242},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.6051199436187744},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.584166944026947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5797218084335327},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4872373640537262},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3948003053665161},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.340518593788147},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07731172442436218}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.817233145236969},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6952564120292664},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6228971481323242},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.6051199436187744},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.584166944026947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5797218084335327},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4872373640537262},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3948003053665161},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.340518593788147},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07731172442436218},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1017/s0890060423000197","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s0890060423000197","pdf_url":null,"source":{"id":"https://openalex.org/S4210193102","display_name":"Artificial intelligence for engineering design analysis and manufacturing","issn_l":"0890-0604","issn":["0890-0604","1469-1760"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence for Engineering Design, Analysis and Manufacturing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G8842227510","display_name":null,"funder_award_id":"52075111","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":29,"referenced_works":["https://openalex.org/W243674440","https://openalex.org/W2194775991","https://openalex.org/W2529693955","https://openalex.org/W2556345765","https://openalex.org/W2595657631","https://openalex.org/W2744790985","https://openalex.org/W2768753204","https://openalex.org/W2791694051","https://openalex.org/W2887782657","https://openalex.org/W2936912529","https://openalex.org/W2940259008","https://openalex.org/W2940491215","https://openalex.org/W2947583263","https://openalex.org/W2977117446","https://openalex.org/W2998506103","https://openalex.org/W3007485446","https://openalex.org/W3014615236","https://openalex.org/W3014644090","https://openalex.org/W3042706401","https://openalex.org/W3098362015","https://openalex.org/W3135644512","https://openalex.org/W4210325776","https://openalex.org/W4210985339","https://openalex.org/W4214919980","https://openalex.org/W4285064815","https://openalex.org/W4285245107","https://openalex.org/W4310423857","https://openalex.org/W4313459845","https://openalex.org/W4361249171"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2035937180","https://openalex.org/W3196220745","https://openalex.org/W3097502728","https://openalex.org/W2575656761","https://openalex.org/W2065631063","https://openalex.org/W2378667342","https://openalex.org/W2372829958","https://openalex.org/W2594567802","https://openalex.org/W2363739414"],"abstract_inverted_index":{"Abstract":[0],"Deep":[1],"learning":[2,31],"(DL)":[3],"has":[4,176],"been":[5],"widely":[6],"used":[7],"in":[8,39],"bearing":[9,63],"fault":[10,24,37,64,144,166],"diagnosis.":[11,65,145],"In":[12],"particular,":[13],"convolutional":[14],"neural":[15,59],"networks":[16],"(CNNs)":[17],"improve":[18,165],"diagnosis":[19,45,167],"accuracy":[20,168],"by":[21],"extracting":[22],"excellent":[23,177],"features.":[25,119,129],"However,":[26],"CNN":[27,122],"lacks":[28],"an":[29],"explicit":[30],"mechanism":[32],"to":[33,43,88,106,115],"distinguish":[34],"between":[35],"different":[36,154],"characteristics":[38],"the":[40,44,92,96,108,116,121,131,138,149,160,171],"input":[41,117],"signal":[42],"results.":[46],"This":[47],"article":[48],"presents":[49],"a":[50,69],"new":[51],"end-to-end":[52],"depth":[53],"framework":[54],"called":[55],"multi-head":[56,100],"self-attention":[57,101],"convolution":[58],"network":[60],"(MSA-CNN)":[61],"for":[62,143],"Firstly,":[66],"we":[67],"adopt":[68],"data":[70],"pre-processing":[71],"method":[72],"that":[73,159],"directly":[74],"converts":[75],"one-dimensional":[76],"(1D)":[77],"original":[78,97],"signals":[79],"into":[80,137],"two-dimensional":[81],"(2D)":[82],"grayscale":[83],"images,":[84],"which":[85],"is":[86,103,151],"simple":[87],"implement":[89],"and":[90,111,175],"preserves":[91],"complete":[93],"information":[94,110],"of":[95,148],"signal.":[98],"Secondly,":[99],"(MSA)":[102],"first":[104],"constructed":[105],"aggregate":[107],"global":[109],"adaptively":[112],"assign":[113],"weights":[114],"signal's":[118],"Thirdly,":[120],"with":[123,170],"small-scale":[124],"kernels":[125],"extracted":[126],"detailed":[127],"local":[128],"Finally,":[130],"learned":[132],"high-level":[133],"representations":[134],"are":[135],"fed":[136],"full":[139],"connect":[140],"(FC)":[141],"layer":[142],"The":[146,156],"performance":[147],"MSA-CNN":[150,162],"validated":[152],"on":[153],"datasets.":[155],"results":[157],"show":[158],"proposed":[161],"can":[163],"significantly":[164],"compared":[169],"other":[172],"state-of-the-art":[173],"methods":[174],"noise":[178],"immunity":[179],"performance.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
