{"id":"https://openalex.org/W4288058759","doi":"https://doi.org/10.1080/00207543.2022.2032860","title":"A novel self-training semi-supervised deep learning approach for machinery fault diagnosis","display_name":"A novel self-training semi-supervised deep learning approach for machinery fault diagnosis","publication_year":2022,"publication_date":"2022-02-14","ids":{"openalex":"https://openalex.org/W4288058759","doi":"https://doi.org/10.1080/00207543.2022.2032860"},"language":"en","primary_location":{"id":"doi:10.1080/00207543.2022.2032860","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00207543.2022.2032860","pdf_url":null,"source":{"id":"https://openalex.org/S65690446","display_name":"International Journal of Production Research","issn_l":"0020-7543","issn":["0020-7543","1366-588X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Production Research","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/A5043140947","display_name":"Jianyu Long","orcid":"https://orcid.org/0000-0002-5173-1159"},"institutions":[{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianyu Long","raw_affiliation_strings":["School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People\u2019s Republic of China","School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People's Republic of China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People\u2019s Republic of China","institution_ids":["https://openalex.org/I2799850029"]},{"raw_affiliation_string":"School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People's Republic of China","institution_ids":["https://openalex.org/I2799850029"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101996550","display_name":"Yibin Chen","orcid":"https://orcid.org/0009-0004-0587-0379"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibin Chen","raw_affiliation_strings":["College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, People\u2019s Republic of China","School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People\u2019s Republic of China","School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People's Republic of China","College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, People's Republic of China"],"affiliations":[{"raw_affiliation_string":"College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, People\u2019s Republic of China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People\u2019s Republic of China","institution_ids":["https://openalex.org/I2799850029"]},{"raw_affiliation_string":"School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People's Republic of China","institution_ids":["https://openalex.org/I2799850029"]},{"raw_affiliation_string":"College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, People's Republic of China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091588045","display_name":"Zhe Yang","orcid":"https://orcid.org/0000-0002-4881-0008"},"institutions":[{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Yang","raw_affiliation_strings":["School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People\u2019s Republic of China","School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People's Republic of China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People\u2019s Republic of China","institution_ids":["https://openalex.org/I2799850029"]},{"raw_affiliation_string":"School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People's Republic of China","institution_ids":["https://openalex.org/I2799850029"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045740528","display_name":"Yunwei Huang","orcid":"https://orcid.org/0000-0002-0411-799X"},"institutions":[{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunwei Huang","raw_affiliation_strings":["School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People\u2019s Republic of China","School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People's Republic of China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People\u2019s Republic of China","institution_ids":["https://openalex.org/I2799850029"]},{"raw_affiliation_string":"School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People's Republic of China","institution_ids":["https://openalex.org/I2799850029"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100404427","display_name":"Chuan Li","orcid":"https://orcid.org/0000-0003-0004-1497"},"institutions":[{"id":"https://openalex.org/I2799850029","display_name":"Dongguan University of Technology","ror":"https://ror.org/01m8p7q42","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799850029"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chuan Li","raw_affiliation_strings":["School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People\u2019s Republic of China","School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People's Republic of China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People\u2019s Republic of China","institution_ids":["https://openalex.org/I2799850029"]},{"raw_affiliation_string":"School of Mechanical Engineering, Dongguan University of Technology, Dongguan, People's Republic of China","institution_ids":["https://openalex.org/I2799850029"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100404427"],"corresponding_institution_ids":["https://openalex.org/I2799850029"],"apc_list":null,"apc_paid":null,"fwci":10.7224,"has_fulltext":false,"cited_by_count":93,"citation_normalized_percentile":{"value":0.99111804,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"61","issue":"23","first_page":"8238","last_page":"8251"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9988999962806702,"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":0.9988999962806702,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.982699990272522,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.968999981880188,"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/classifier","display_name":"Classifier (UML)","score":0.6276347637176514},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6223869323730469},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.509566068649292},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5037407279014587},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.49188733100891113},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46595367789268494},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4633833169937134},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4354904890060425},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.41938716173171997},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.27998441457748413}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6276347637176514},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6223869323730469},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.509566068649292},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5037407279014587},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.49188733100891113},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46595367789268494},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4633833169937134},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4354904890060425},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.41938716173171997},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27998441457748413},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/00207543.2022.2032860","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00207543.2022.2032860","pdf_url":null,"source":{"id":"https://openalex.org/S65690446","display_name":"International Journal of Production Research","issn_l":"0020-7543","issn":["0020-7543","1366-588X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Production Research","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:taf:tprsxx:v:61:y:2023:i:23:p:8238-8251","is_oa":false,"landing_page_url":"http://hdl.handle.net/10.1080/00207543.2022.2032860","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.44999998807907104,"display_name":"Partnerships for the goals"}],"awards":[{"id":"https://openalex.org/G1687578602","display_name":null,"funder_award_id":"72171049","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4864091059","display_name":null,"funder_award_id":"52175080","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7473214046","display_name":null,"funder_award_id":"2019B1515120095","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G8872710766","display_name":null,"funder_award_id":"52005103","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"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1597576211","https://openalex.org/W1988529147","https://openalex.org/W2002409680","https://openalex.org/W2048679005","https://openalex.org/W2079057609","https://openalex.org/W2097089247","https://openalex.org/W2104290444","https://openalex.org/W2107968230","https://openalex.org/W2549144957","https://openalex.org/W2588516144","https://openalex.org/W2592691248","https://openalex.org/W2756689160","https://openalex.org/W2765569127","https://openalex.org/W2767031373","https://openalex.org/W2777300582","https://openalex.org/W2810791100","https://openalex.org/W2896451001","https://openalex.org/W2918050063","https://openalex.org/W2942245950","https://openalex.org/W2952273139","https://openalex.org/W2953070460","https://openalex.org/W2963975998","https://openalex.org/W2963989829","https://openalex.org/W2973093569","https://openalex.org/W2977117446","https://openalex.org/W2997701990","https://openalex.org/W2998506103","https://openalex.org/W3009811754","https://openalex.org/W3010931250","https://openalex.org/W3039216919","https://openalex.org/W3081074546","https://openalex.org/W3083796308","https://openalex.org/W3087233860","https://openalex.org/W3095770430","https://openalex.org/W3110992226","https://openalex.org/W3149994345","https://openalex.org/W3154040793","https://openalex.org/W3154691472","https://openalex.org/W3155400606","https://openalex.org/W6676348322"],"related_works":["https://openalex.org/W1185300216","https://openalex.org/W2954163146","https://openalex.org/W2899086345","https://openalex.org/W2896057011","https://openalex.org/W2115336194","https://openalex.org/W4238675884","https://openalex.org/W2389652943","https://openalex.org/W2007713238","https://openalex.org/W4231537015","https://openalex.org/W2137791473"],"abstract_inverted_index":{"Fault":[0],"diagnosis":[1,20,55],"is":[2,49,69,120,151],"an":[3],"indispensable":[4],"basis":[5],"for":[6,145,157],"the":[7,25,79,85,98,105,126,138,142,155,172,181],"collaborative":[8],"maintenance":[9],"in":[10,24,111,122,171],"prognostic":[11],"and":[12,61,82],"health":[13],"management.":[14],"Most":[15],"of":[16,27,35,128,136],"existing":[17,112],"data-driven":[18],"fault":[19,54],"approaches":[21],"are":[22],"designed":[23,152],"framework":[26],"supervised":[28],"learning,":[29],"which":[30],"requires":[31],"a":[32,41,53,73,89,116,147],"large":[33],"number":[34,127],"labelled":[36,60,80,164],"samples.":[37,64],"In":[38,133],"this":[39],"paper,":[40],"novel":[42],"self-training":[43,113,193],"semi-supervised":[44,114,194],"deep":[45,173],"learning":[46,195],"(SSDL)":[47],"approach":[48,68,184],"proposed":[50,121,182],"to":[51,124,153,191],"train":[52],"model":[56],"together":[57],"with":[58,92],"few":[59,90],"abundant":[62],"unlabelled":[63,99,159],"The":[65,176],"addressed":[66],"SSDL":[67,123,183],"realised":[70],"by":[71,102,161],"initialising":[72],"stacked":[74],"sparse":[75],"auto-encoder":[76],"classifier":[77,86],"using":[78,137],"samples,":[81],"subsequently":[83],"updating":[84],"via":[87],"sampling":[88,109,149],"candidates":[91,131],"most":[93],"reliable":[94],"pseudo":[95],"labels":[96],"from":[97],"samples":[100],"step":[101],"step.":[103],"Unlike":[104],"commonly":[106],"used":[107],"static":[108],"strategy":[110],"frameworks,":[115],"gradually":[117],"exploiting":[118],"mechanism":[119],"increase":[125],"selected":[129],"pseudo-labelled":[130],"gradually.":[132],"addition,":[134],"instead":[135],"prediction":[139,188],"accuracy":[140,189],"as":[141],"confidence":[143],"estimation":[144],"pseudo-labels,":[146],"distance-based":[148],"criterion":[150],"assign":[154],"label":[156],"each":[158],"sample":[160,165],"its":[162],"nearest":[163],"based":[166],"on":[167],"their":[168],"Euclidean":[169],"distances":[170],"feature":[174],"space.":[175],"experimental":[177],"results":[178],"show":[179],"that":[180],"can":[185],"achieve":[186],"good":[187],"compared":[190],"other":[192],"algorithms.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":11}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
