{"id":"https://openalex.org/W4285117135","doi":"https://doi.org/10.1109/tii.2022.3183225","title":"A Compressed Unsupervised Deep Domain Adaptation Model for Efficient Cross-Domain Fault Diagnosis","display_name":"A Compressed Unsupervised Deep Domain Adaptation Model for Efficient Cross-Domain Fault Diagnosis","publication_year":2022,"publication_date":"2022-06-15","ids":{"openalex":"https://openalex.org/W4285117135","doi":"https://doi.org/10.1109/tii.2022.3183225"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2022.3183225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2022.3183225","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/A5084696020","display_name":"Gaowei Xu","orcid":"https://orcid.org/0000-0003-3752-7749"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gaowei Xu","raw_affiliation_strings":["School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0003-3752-7749","affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009018575","display_name":"Chenxi Huang","orcid":"https://orcid.org/0000-0002-2100-0259"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenxi Huang","raw_affiliation_strings":["School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0002-2100-0259","affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012180559","display_name":"Daniel S. da Silva","orcid":"https://orcid.org/0000-0001-5670-1496"},"institutions":[{"id":"https://openalex.org/I243754102","display_name":"Universidade Federal do Cear\u00e1","ror":"https://ror.org/03srtnf24","country_code":"BR","type":"education","lineage":["https://openalex.org/I243754102"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Daniel Santos da Silva","raw_affiliation_strings":["Department of Teleinformatics Engineering, Federal University of Cear&#x00E1;, Fortaleza, Brazil"],"raw_orcid":"https://orcid.org/0000-0001-5670-1496","affiliations":[{"raw_affiliation_string":"Department of Teleinformatics Engineering, Federal University of Cear&#x00E1;, Fortaleza, Brazil","institution_ids":["https://openalex.org/I243754102"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045093520","display_name":"Victor Hugo C. de Albuquerque","orcid":"https://orcid.org/0000-0003-3886-4309"},"institutions":[{"id":"https://openalex.org/I243754102","display_name":"Universidade Federal do Cear\u00e1","ror":"https://ror.org/03srtnf24","country_code":"BR","type":"education","lineage":["https://openalex.org/I243754102"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Victor Hugo C. de Albuquerque","raw_affiliation_strings":["Department of Teleinformatics Engineering, Federal University of Cear&#x00E1;, Fortaleza, Brazil"],"raw_orcid":"https://orcid.org/0000-0003-3886-4309","affiliations":[{"raw_affiliation_string":"Department of Teleinformatics Engineering, Federal University of Cear&#x00E1;, Fortaleza, Brazil","institution_ids":["https://openalex.org/I243754102"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.278,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.96322523,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"19","issue":"5","first_page":"6741","last_page":"6749"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9958999752998352,"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":0.9958999752998352,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9940000176429749,"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/T13050","display_name":"Oil and Gas Production Techniques","score":0.9574000239372253,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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":0.7754424810409546},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6231731176376343},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5644530057907104},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5446966290473938},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.49701836705207825},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49640899896621704},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4746711254119873},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.43093931674957275},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4164677560329437},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38906678557395935},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3856990933418274},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3448367714881897}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7754424810409546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6231731176376343},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5644530057907104},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5446966290473938},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.49701836705207825},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49640899896621704},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4746711254119873},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43093931674957275},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4164677560329437},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38906678557395935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3856990933418274},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3448367714881897},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2022.3183225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2022.3183225","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":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4099999964237213}],"awards":[{"id":"https://openalex.org/G833345558","display_name":null,"funder_award_id":"62002304","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":31,"referenced_works":["https://openalex.org/W1973150690","https://openalex.org/W2250853501","https://openalex.org/W2530806392","https://openalex.org/W2612554669","https://openalex.org/W2763583057","https://openalex.org/W2768753204","https://openalex.org/W2897295818","https://openalex.org/W2898375427","https://openalex.org/W2919115771","https://openalex.org/W2920611841","https://openalex.org/W2943925420","https://openalex.org/W2946048316","https://openalex.org/W2954075188","https://openalex.org/W2957568672","https://openalex.org/W2964233199","https://openalex.org/W2965604235","https://openalex.org/W2965862774","https://openalex.org/W2969372261","https://openalex.org/W2970958999","https://openalex.org/W2976153356","https://openalex.org/W2978274700","https://openalex.org/W2984201918","https://openalex.org/W2990063867","https://openalex.org/W2993091699","https://openalex.org/W2993397516","https://openalex.org/W2996386983","https://openalex.org/W2998506103","https://openalex.org/W3025888249","https://openalex.org/W3142041738","https://openalex.org/W3164351180","https://openalex.org/W6772186950"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2373300491","https://openalex.org/W4375867731","https://openalex.org/W2395294869","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"As":[0],"one":[1],"of":[2,21,35,43,57,99,122,149],"the":[3,15,22,33,39,82,97,107,116,119,125,133,138,150,156,167,173,183],"most":[4,56],"important":[5],"artificial":[6],"intelligence-enabled":[7],"industrial":[8,52],"applications,":[9],"fault":[10,28,59,75],"diagnosis":[11,29,60,76],"is":[12,38,47,78,93,112,128,142,153],"vital":[13],"in":[14,50],"safe,":[16],"stable,":[17],"and":[18,65,102,178],"reliable":[19],"operation":[20],"equipment.":[23],"Many":[24],"existing":[25],"deep":[26,71],"learning-based":[27],"methods":[30,61],"assume":[31],"that":[32,42,166],"distribution":[34],"training":[36,100],"data":[37,101],"same":[40],"as":[41],"testing":[44,103],"data,":[45,104],"which":[46],"almost":[48],"impossible":[49],"practical":[51],"applications.":[53],"In":[54],"addition,":[55],"these":[58],"are":[62],"generally":[63],"memory-intensive":[64],"computationally":[66],"expensive.":[67],"A":[68],"compressed":[69,129,140,168],"unsupervised":[70,89],"domain":[72,90],"adaption":[73,91],"model-based":[74],"method":[77,152],"proposed":[79,151],"to":[80,95,114,144],"overcome":[81],"abovementioned":[83],"two":[84],"issues.":[85],"First,":[86],"a":[87],"standard":[88,126,184],"model":[92,127,141,169],"designed":[94],"extract":[96],"features":[98,121],"respectively.":[105],"Then,":[106],"maximum":[108],"mean":[109],"discrepancy":[110,117],"term":[111],"introduced":[113],"minimize":[115],"between":[118],"extracted":[120],"them.":[123],"Next,":[124],"through":[130],"iteratively":[131],"pruning":[132],"redundant":[134],"convolutional":[135],"channels.":[136],"Finally,":[137],"obtained":[139],"applied":[143],"diagnose":[145],"faults.":[146],"The":[147],"performance":[148],"verified":[154],"on":[155,194],"Case":[157],"Western":[158],"Reserve":[159],"University":[160],"bearing":[161],"dataset.":[162],"Experimental":[163],"results":[164],"show":[165],"can":[170],"significantly":[171],"reduce":[172],"memory":[174],"occupation,":[175],"computational":[176],"cost,":[177],"inference":[179],"time":[180],"compared":[181],"with":[182],"model,":[185],"but":[186],"still":[187],"achieve":[188],"comparable":[189],"or":[190],"even":[191],"better":[192],"accuracy":[193],"ten":[195],"transfer":[196],"diagnostic":[197],"tasks.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
