{"id":"https://openalex.org/W4392173929","doi":"https://doi.org/10.1109/tii.2024.3363189","title":"Supervised Contrastive Learning for Multisensor Signals Classification in Automobile Engine Manufacturing","display_name":"Supervised Contrastive Learning for Multisensor Signals Classification in Automobile Engine Manufacturing","publication_year":2024,"publication_date":"2024-02-26","ids":{"openalex":"https://openalex.org/W4392173929","doi":"https://doi.org/10.1109/tii.2024.3363189"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2024.3363189","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3363189","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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/A5017341766","display_name":"Yoon Sang Cho","orcid":"https://orcid.org/0000-0001-5420-3434"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]},{"id":"https://openalex.org/I2799503643","display_name":"Columbia University Irving Medical Center","ror":"https://ror.org/01esghr10","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I2799503643"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["KR","US"],"is_corresponding":true,"raw_author_name":"Yoon Sang Cho","raw_affiliation_strings":["Korea University, Seoul, South Korea","New York University Medical Center, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0001-5420-3434","affiliations":[{"raw_affiliation_string":"Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"New York University Medical Center, New York, NY, USA","institution_ids":["https://openalex.org/I2799503643","https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058258354","display_name":"Seoung Bum Kim","orcid":"https://orcid.org/0000-0002-2205-8516"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seoung Bum Kim","raw_affiliation_strings":["Korea University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-2205-8516","affiliations":[{"raw_affiliation_string":"Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017341766"],"corresponding_institution_ids":["https://openalex.org/I197347611","https://openalex.org/I2799503643","https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":1.5108,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81133428,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"20","issue":"5","first_page":"7764","last_page":"7776"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.996399998664856,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.996399998664856,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.989799976348877,"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/T12282","display_name":"Mineral Processing and Grinding","score":0.9876999855041504,"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/computer-science","display_name":"Computer science","score":0.5891352295875549},{"id":"https://openalex.org/keywords/automotive-engine","display_name":"Automotive engine","score":0.5610734224319458},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46892672777175903},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44523507356643677},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.42473167181015015},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.38153839111328125},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.363467276096344},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3573116958141327}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5891352295875549},{"id":"https://openalex.org/C56238396","wikidata":"https://www.wikidata.org/wiki/Q4056355","display_name":"Automotive engine","level":2,"score":0.5610734224319458},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46892672777175903},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44523507356643677},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.42473167181015015},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.38153839111328125},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.363467276096344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3573116958141327}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2024.3363189","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3363189","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3357278912","display_name":null,"funder_award_id":"2022R1A6A3A03054796","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G8191624576","display_name":null,"funder_award_id":"RS-2022-00144190","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1897892887","https://openalex.org/W2051463173","https://openalex.org/W2059518577","https://openalex.org/W2084327162","https://openalex.org/W2194775991","https://openalex.org/W2562762876","https://openalex.org/W2589171657","https://openalex.org/W2594332903","https://openalex.org/W2603304445","https://openalex.org/W2740570963","https://openalex.org/W2789904726","https://openalex.org/W2810292802","https://openalex.org/W2888477829","https://openalex.org/W2890207295","https://openalex.org/W2965373594","https://openalex.org/W2977117446","https://openalex.org/W3000983008","https://openalex.org/W3007212997","https://openalex.org/W3007888802","https://openalex.org/W3025867661","https://openalex.org/W3033437210","https://openalex.org/W3038010422","https://openalex.org/W3045935064","https://openalex.org/W3046296398","https://openalex.org/W3047895608","https://openalex.org/W3049307721","https://openalex.org/W3120795858","https://openalex.org/W3179317353","https://openalex.org/W3192807145","https://openalex.org/W3194501256","https://openalex.org/W4241570161","https://openalex.org/W4287614078","https://openalex.org/W4287812705","https://openalex.org/W4289360400","https://openalex.org/W4362724932","https://openalex.org/W6637373629","https://openalex.org/W6755529311","https://openalex.org/W6766673545","https://openalex.org/W6774314701","https://openalex.org/W6776700526","https://openalex.org/W6784874100"],"related_works":["https://openalex.org/W2601157893","https://openalex.org/W2373006798","https://openalex.org/W2359109991","https://openalex.org/W2131735617","https://openalex.org/W2056912418","https://openalex.org/W2033213769","https://openalex.org/W4312376745","https://openalex.org/W2136016640","https://openalex.org/W2049538278","https://openalex.org/W2886173746"],"abstract_inverted_index":{"Classification":[0],"of":[1,21,28,53,72,117],"multisensor":[2,61,73,142],"signals":[3],"is":[4],"an":[5],"important":[6],"problem":[7],"in":[8,14,149],"maintaining":[9],"stable":[10],"process":[11],"operations,":[12],"particularly":[13],"advancing":[15],"predictive":[16],"modeling":[17,60],"for":[18,59,69,83,120,141],"early":[19,121,146],"detection":[20,148],"abnormal":[22],"states.":[23],"Self-supervised":[24],"learning":[25,67,105],"methods,":[26],"one":[27],"the":[29,51,70,94,114],"representation":[30],"learnings,":[31],"have":[32,38],"been":[33],"widely":[34],"studied.":[35],"However,":[36],"they":[37],"focused":[39],"on":[40],"using":[41],"unlabeled":[42],"data.":[43],"In":[44],"this":[45],"study,":[46],"we":[47,112],"aim":[48],"to":[49],"address":[50],"challenge":[52],"effectively":[54],"utilizing":[55],"fully":[56],"labeled":[57],"data":[58,88,129],"signals.":[62,74],"We":[63],"introduce":[64],"supervised":[65,104],"contrastive":[66],"(SCL)":[68],"classification":[71],"Our":[75,97,135],"training":[76,92],"framework":[77],"involves":[78],"a":[79,108,138],"two-step":[80],"process:":[81],"SCL":[82],"encoder":[84],"pretraining":[85],"with":[86,93,127],"time-series":[87],"augmentations,":[89],"and":[90,145],"classifier":[91],"pretrained":[95],"encoder.":[96],"method":[98,140],"exhibits":[99],"superior":[100],"performance,":[101],"outperforming":[102],"traditional":[103],"approaches":[106],"by":[107],"substantial":[109],"margin.":[110],"Furthermore,":[111],"demonstrate":[113],"practical":[115],"applicability":[116],"our":[118],"approach":[119],"prediction":[122],"problems":[123],"through":[124],"experiments":[125],"conducted":[126],"real-process":[128],"obtained":[130],"from":[131],"automobile":[132],"engine":[133],"manufacturing.":[134],"work":[136],"offers":[137],"promising":[139],"signal":[143],"analysis":[144],"fault":[147],"manufacturing":[150],"industries.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-05-20T08:49:12.498775","created_date":"2025-10-10T00:00:00"}