{"id":"https://openalex.org/W4412081726","doi":"https://doi.org/10.1109/jiot.2025.3586718","title":"Semi-Supervised Federated Learning via Dual Contrastive Learning and Soft Labeling for Intelligent Fault Diagnosis","display_name":"Semi-Supervised Federated Learning via Dual Contrastive Learning and Soft Labeling for Intelligent Fault Diagnosis","publication_year":2025,"publication_date":"2025-07-07","ids":{"openalex":"https://openalex.org/W4412081726","doi":"https://doi.org/10.1109/jiot.2025.3586718"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2025.3586718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3586718","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.14181","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101762639","display_name":"Yajiao Dai","orcid":"https://orcid.org/0009-0002-0868-4112"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yajiao Dai","raw_affiliation_strings":["School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0002-0868-4112","affiliations":[{"raw_affiliation_string":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100691319","display_name":"Jun Li","orcid":"https://orcid.org/0000-0002-6239-2922"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["School of Information Science and Engineering, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-6239-2922","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007513378","display_name":"Zhen Mei","orcid":"https://orcid.org/0000-0002-9769-0604"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Mei","raw_affiliation_strings":["School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-9769-0604","affiliations":[{"raw_affiliation_string":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068307922","display_name":"Yiyang Ni","orcid":"https://orcid.org/0000-0001-5893-6854"},"institutions":[{"id":"https://openalex.org/I235331625","display_name":"Jiangsu Second Normal University","ror":"https://ror.org/00e6ytg41","country_code":"CN","type":"education","lineage":["https://openalex.org/I235331625"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiyang Ni","raw_affiliation_strings":["Institute of Artificial Intelligence Research, Jiangsu Second Normal University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-5893-6854","affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence Research, Jiangsu Second Normal University, Nanjing, China","institution_ids":["https://openalex.org/I235331625"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013079905","display_name":"Shi Jin","orcid":"https://orcid.org/0000-0003-0271-6021"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shi Jin","raw_affiliation_strings":["School of Information Science and Engineering, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-0271-6021","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056859236","display_name":"Zengxiang Li","orcid":"https://orcid.org/0000-0002-1462-9905"},"institutions":[{"id":"https://openalex.org/I4210100528","display_name":"ENN (China)","ror":"https://ror.org/018a8yy17","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210100528"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zengxiang Li","raw_affiliation_strings":["Digital Research Institute, ENN Group, Langfang, China"],"raw_orcid":"https://orcid.org/0000-0002-1462-9905","affiliations":[{"raw_affiliation_string":"Digital Research Institute, ENN Group, Langfang, China","institution_ids":["https://openalex.org/I4210100528"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100687093","display_name":"Sheng Guo","orcid":"https://orcid.org/0000-0001-5493-3664"},"institutions":[{"id":"https://openalex.org/I4210100528","display_name":"ENN (China)","ror":"https://ror.org/018a8yy17","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210100528"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Guo","raw_affiliation_strings":["Digital Research Institute, ENN Group, Langfang, China"],"raw_orcid":"https://orcid.org/0000-0001-5493-3664","affiliations":[{"raw_affiliation_string":"Digital Research Institute, ENN Group, Langfang, China","institution_ids":["https://openalex.org/I4210100528"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100389005","display_name":"Wei Xiang","orcid":"https://orcid.org/0000-0002-0608-065X"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wei Xiang","raw_affiliation_strings":["School of Computing, Engineering and Mathematical Sciences, La Trobe University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-0608-065X","affiliations":[{"raw_affiliation_string":"School of Computing, Engineering and Mathematical Sciences, La Trobe University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I196829312"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.188,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.93961398,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"12","issue":"18","first_page":"38352","last_page":"38365"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9672999978065491,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9672999978065491,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9182000160217285,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9146000146865845,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.807863712310791},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.6572589874267578},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5184156894683838},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4214560389518738},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4171258807182312},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3282928168773651}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.807863712310791},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6572589874267578},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5184156894683838},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4214560389518738},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4171258807182312},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3282928168773651},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"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/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/jiot.2025.3586718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3586718","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2507.14181","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.14181","pdf_url":"https://arxiv.org/pdf/2507.14181","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"pmh:oai:researchonline.jcu.edu.au:88665","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196350","display_name":"ResearchOnline - JCU (James Cook University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I86467917","host_organization_name":"James Cook University","host_organization_lineage":["https://openalex.org/I86467917"],"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":{"id":"pmh:oai:arXiv.org:2507.14181","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.14181","pdf_url":"https://arxiv.org/pdf/2507.14181","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2637521528","display_name":null,"funder_award_id":"62471204","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3528550281","display_name":null,"funder_award_id":"62201258","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5816773294","display_name":null,"funder_award_id":"30923011035","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W3031466690","https://openalex.org/W3122294042","https://openalex.org/W3190152617","https://openalex.org/W3202645507","https://openalex.org/W3209598599","https://openalex.org/W4213436114","https://openalex.org/W4214688034","https://openalex.org/W4214928119","https://openalex.org/W4285079201","https://openalex.org/W4285283167","https://openalex.org/W4312253507","https://openalex.org/W4312462223","https://openalex.org/W4312691731","https://openalex.org/W4312856136","https://openalex.org/W4320015847","https://openalex.org/W4320713235","https://openalex.org/W4365128729","https://openalex.org/W4365790369","https://openalex.org/W4367671658","https://openalex.org/W4376457039","https://openalex.org/W4380451070","https://openalex.org/W4385489649","https://openalex.org/W4386737174","https://openalex.org/W4387757462","https://openalex.org/W4388407698","https://openalex.org/W4388878683","https://openalex.org/W4389513550","https://openalex.org/W4390120136","https://openalex.org/W4392901727","https://openalex.org/W4393154273","https://openalex.org/W4399039452","https://openalex.org/W4401023535","https://openalex.org/W4401025048","https://openalex.org/W4402350447","https://openalex.org/W4404035333","https://openalex.org/W4407639499","https://openalex.org/W4408145176","https://openalex.org/W4408304995","https://openalex.org/W4409019594","https://openalex.org/W4409153745","https://openalex.org/W4410115897"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Intelligent":[0],"fault":[1],"diagnosis":[2],"(IFD)":[3],"plays":[4],"a":[5,27,75,137,164,222],"crucial":[6],"role":[7],"in":[8,39,57,155],"ensuring":[9],"the":[10,43,65,114,143,159,193,209,228,231,239,243],"safe":[11],"operation":[12],"of":[13,30,45,238],"industrial":[14],"machinery":[15],"and":[16,33,86,92,117,130,183,198,221],"improving":[17],"production":[18],"efficiency.":[19],"However,":[20],"traditional":[21],"supervised":[22],"deep":[23],"learning":[24,78,109,120],"methods":[25],"require":[26],"large":[28],"amount":[29],"training":[31,161],"data":[32,46,58,91,112,177,240],"labels,":[34],"which":[35,81],"are":[36,190,214,241],"often":[37],"located":[38],"different":[40,176],"clients.":[41,206],"Additionally,":[42],"cost":[44],"labeling":[47,88],"is":[48,146,168],"high,":[49],"making":[50],"labels":[51,157],"difficult":[52],"to":[53,89,148,170,202,251],"acquire.":[54],"Meanwhile,":[55],"differences":[56],"distribution":[59,145],"among":[60,121,205],"clients":[61,97,122],"may":[62],"also":[63],"hinder":[64],"model\u2019s":[66],"performance.":[67],"To":[68,207],"tackle":[69],"these":[70],"challenges,":[71],"this":[72],"paper":[73],"proposes":[74],"semi-supervised":[76,160],"federated":[77],"framework,":[79,212],"SSFL-DCSL,":[80],"integrates":[82],"dual":[83,165],"contrastive":[84,166,181,185],"loss":[85,167,182],"soft":[87],"address":[90],"label":[93],"scarcity":[94],"for":[95],"distributed":[96],"with":[98,195,200],"few":[99],"labeled":[100],"samples":[101],"while":[102],"safeguarding":[103],"user":[104],"privacy.":[105],"It":[106],"enables":[107],"representation":[108],"using":[110],"unlabeled":[111],"on":[113,142,192,216,225],"client":[115],"side":[116],"facilitates":[118],"joint":[119],"through":[123],"prototypes,":[124],"thereby":[125],"achieving":[126],"mutual":[127],"knowledge":[128,204],"sharing":[129],"preventing":[131],"local":[132,180,188],"model":[133,172],"divergence.":[134],"Specifically,":[135],"first,":[136],"sample":[138],"weighting":[139],"function":[140],"based":[141],"Laplace":[144],"designed":[147],"alleviate":[149],"bias":[150],"caused":[151,174],"by":[152,175,249],"low":[153],"confidence":[154],"pseudo":[156],"during":[158],"process.":[162],"Second,":[163],"introduced":[169],"mitigate":[171],"divergence":[173],"distributions,":[178],"comprising":[179],"global":[184],"loss.":[186],"Third,":[187],"prototypes":[189],"aggregated":[191],"server":[194],"weighted":[196],"averaging":[197],"updated":[199],"momentum":[201],"share":[203],"evaluate":[208],"proposed":[210,244],"SSFL-DCSL":[211,245],"experiments":[213],"conducted":[215],"two":[217],"publicly":[218],"available":[219],"datasets":[220],"dataset":[223],"collected":[224],"motors":[226],"from":[227],"factory.":[229],"In":[230],"most":[232],"challenging":[233],"task,":[234],"where":[235],"only":[236],"10%":[237],"labeled,":[242],"can":[246],"improve":[247],"accuracy":[248],"1.15%":[250],"7.85%":[252],"over":[253],"state-of-the-art":[254],"methods.":[255]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
