{"id":"https://openalex.org/W4395056627","doi":"https://doi.org/10.1109/tii.2024.3384603","title":"Cross-Domain Compound Fault Diagnosis of Machine-Level Motors via Time\u2013Frequency Self-Contrastive Learning","display_name":"Cross-Domain Compound Fault Diagnosis of Machine-Level Motors via Time\u2013Frequency Self-Contrastive Learning","publication_year":2024,"publication_date":"2024-04-23","ids":{"openalex":"https://openalex.org/W4395056627","doi":"https://doi.org/10.1109/tii.2024.3384603"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2024.3384603","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3384603","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/A5059273157","display_name":"Yiming He","orcid":"https://orcid.org/0000-0002-6156-3507"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiming He","raw_affiliation_strings":["State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-6156-3507","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011621973","display_name":"Chao Zhao","orcid":"https://orcid.org/0000-0002-1749-7223"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Zhao","raw_affiliation_strings":["State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-1749-7223","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062049138","display_name":"Weiming Shen","orcid":"https://orcid.org/0000-0001-5204-7992"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiming Shen","raw_affiliation_strings":["State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-5204-7992","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":13.8485,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.99382336,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"20","issue":"7","first_page":"9692","last_page":"9701"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9991999864578247,"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":0.9991999864578247,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9958000183105469,"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":0.9819999933242798,"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/frequency-domain","display_name":"Frequency domain","score":0.5377488136291504},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5205303430557251},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4538908004760742},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.4218599796295166},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.4199501574039459},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39761584997177124},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3402916491031647},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.19449388980865479},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.1575133204460144}],"concepts":[{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5377488136291504},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5205303430557251},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4538908004760742},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.4218599796295166},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.4199501574039459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39761584997177124},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3402916491031647},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.19449388980865479},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.1575133204460144},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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:10.1109/tii.2024.3384603","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3384603","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/G2304302389","display_name":null,"funder_award_id":"U20A6004","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2744790985","https://openalex.org/W2994433718","https://openalex.org/W3101729775","https://openalex.org/W3133856501","https://openalex.org/W3152682522","https://openalex.org/W3157688629","https://openalex.org/W3196436997","https://openalex.org/W3212889265","https://openalex.org/W4213075002","https://openalex.org/W4213290494","https://openalex.org/W4213416527","https://openalex.org/W4214579459","https://openalex.org/W4214928119","https://openalex.org/W4220864965","https://openalex.org/W4285216649","https://openalex.org/W4292321560","https://openalex.org/W4295529416","https://openalex.org/W4295956768","https://openalex.org/W4309686983","https://openalex.org/W4311421422","https://openalex.org/W4311897638","https://openalex.org/W4312846187","https://openalex.org/W4313367665","https://openalex.org/W4318070750","https://openalex.org/W4321021151","https://openalex.org/W4323358415","https://openalex.org/W4382281483","https://openalex.org/W4383617438","https://openalex.org/W4386484549"],"related_works":["https://openalex.org/W2320718078","https://openalex.org/W2653530212","https://openalex.org/W2953216818","https://openalex.org/W2030191131","https://openalex.org/W2123899227","https://openalex.org/W1947057263","https://openalex.org/W2355447608","https://openalex.org/W1980067354","https://openalex.org/W2033324903","https://openalex.org/W1978333447"],"abstract_inverted_index":{"Intelligent":[0],"fault":[1,44,56],"diagnosis":[2,57],"of":[3,31,59,86,132],"industrial":[4,126],"motors":[5,61],"under":[6,22,46],"different":[7,23,47],"operating":[8,24,48],"conditions":[9],"is":[10,36,73,140],"a":[11,53],"valuable":[12],"and":[13,33,40,83,93,105,118],"challenging":[14],"topic.":[15],"Compound":[16],"faults":[17],"are":[18,112,122],"inevitable":[19],"to":[20,27,38,75,96,114,142],"occur":[21],"conditions.":[25,49],"Due":[26],"the":[28,87,106],"high":[29],"cost":[30],"dismantling":[32],"testing,":[34],"it":[35],"impractical":[37],"collect":[39],"label":[41],"all":[42],"compound":[43,55],"types":[45],"This":[50],"article":[51],"proposes":[52],"cross-domain":[54,137],"framework":[58],"machine-level":[60],"without":[62],"target":[63],"domain":[64,92,95],"information.":[65],"A":[66],"novel":[67],"time-frequency":[68],"self-contrastive":[69,98],"learning":[70],"(TFSCL)":[71],"strategy":[72,111],"proposed":[74],"enhance":[76],"domain-irrelevant":[77],"feature":[78],"extraction.":[79],"TFSCL":[80,129],"generates":[81],"homogeneous":[82],"heterogeneous":[84],"information":[85,109],"input":[88],"itself":[89],"from":[90],"time":[91],"frequency":[94],"construct":[97],"pairs.":[99],"The":[100],"multiscale":[101],"spatial":[102],"convolution":[103],"structure":[104],"cross":[107],"time\u2013frequency":[108],"interaction":[110],"designed":[113],"further":[115],"provide":[116],"fusion":[117],"interaction.":[119],"Ablation":[120],"experiments":[121],"performed":[123],"on":[124,135],"real":[125],"motor":[127],"signals.":[128],"achieved":[130],"F1-scores":[131],"over":[133],"90%":[134],"six":[136],"tasks,":[138],"which":[139],"superior":[141],"compared":[143],"advanced":[144],"lightweight":[145],"models.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":16},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}