{"id":"https://openalex.org/W3106901053","doi":"https://doi.org/10.1109/tim.2020.3042300","title":"Deep Adversarial Capsule Network for Compound Fault Diagnosis of Machinery Toward Multidomain Generalization Task","display_name":"Deep Adversarial Capsule Network for Compound Fault Diagnosis of Machinery Toward Multidomain Generalization Task","publication_year":2020,"publication_date":"2020-12-03","ids":{"openalex":"https://openalex.org/W3106901053","doi":"https://doi.org/10.1109/tim.2020.3042300","mag":"3106901053"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2020.3042300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3042300","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5082065343","display_name":"Ruyi Huang","orcid":"https://orcid.org/0000-0003-0586-1195"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruyi Huang","raw_affiliation_strings":["School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037156903","display_name":"Jipu Li","orcid":"https://orcid.org/0000-0002-9113-1465"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jipu Li","raw_affiliation_strings":["School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036048287","display_name":"Yixiao Liao","orcid":"https://orcid.org/0000-0002-7040-2182"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixiao Liao","raw_affiliation_strings":["School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082242637","display_name":"Junbin Chen","orcid":"https://orcid.org/0000-0001-6345-5246"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junbin Chen","raw_affiliation_strings":["School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101970242","display_name":"Zhen Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Wang","raw_affiliation_strings":["School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010684849","display_name":"Weihua Li","orcid":"https://orcid.org/0000-0002-7493-1399"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Li","raw_affiliation_strings":["School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5082065343"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":11.7521,"has_fulltext":false,"cited_by_count":218,"citation_normalized_percentile":{"value":0.99086114,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9799000024795532,"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":0.9761999845504761,"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":0.691929280757904},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6739341616630554},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6661038398742676},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5981265306472778},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.49097731709480286},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.45926252007484436},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43241095542907715},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4318097233772278},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.41269588470458984},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3561995029449463},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33290719985961914},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.18425509333610535},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1594005525112152},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09869888424873352}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.691929280757904},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6739341616630554},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6661038398742676},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5981265306472778},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.49097731709480286},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.45926252007484436},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43241095542907715},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4318097233772278},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.41269588470458984},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3561995029449463},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33290719985961914},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.18425509333610535},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1594005525112152},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09869888424873352},{"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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2020.3042300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3042300","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6095112105","display_name":null,"funder_award_id":"51875208","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8969937422","display_name":null,"funder_award_id":"52075182","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1731081199","https://openalex.org/W2104094955","https://openalex.org/W2210061839","https://openalex.org/W2562762876","https://openalex.org/W2747276445","https://openalex.org/W2763583057","https://openalex.org/W2783074568","https://openalex.org/W2789811186","https://openalex.org/W2802633978","https://openalex.org/W2810292802","https://openalex.org/W2887782657","https://openalex.org/W2899279252","https://openalex.org/W2899369559","https://openalex.org/W2900529838","https://openalex.org/W2904138018","https://openalex.org/W2905166565","https://openalex.org/W2906569178","https://openalex.org/W2908441554","https://openalex.org/W2919115771","https://openalex.org/W2921068663","https://openalex.org/W2931035581","https://openalex.org/W2939852233","https://openalex.org/W2940658606","https://openalex.org/W2942682738","https://openalex.org/W2948689530","https://openalex.org/W2949597887","https://openalex.org/W2956467153","https://openalex.org/W2958041981","https://openalex.org/W2961876792","https://openalex.org/W2963703618","https://openalex.org/W2964121744","https://openalex.org/W2968409655","https://openalex.org/W2981982720","https://openalex.org/W2991661665","https://openalex.org/W2998830408","https://openalex.org/W2999663439","https://openalex.org/W2999725011","https://openalex.org/W3005842919","https://openalex.org/W3021496598","https://openalex.org/W3026006566","https://openalex.org/W3037107365","https://openalex.org/W3039055627","https://openalex.org/W3089183752","https://openalex.org/W6631190155","https://openalex.org/W6637618735","https://openalex.org/W6743446608"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4288019534"],"abstract_inverted_index":{"With":[0],"advanced":[1],"measurement":[2],"technologies":[3],"and":[4,20,119,130,160,186,237],"signal":[5],"analytics":[6],"algorithms":[7],"developed":[8],"rapidly,":[9],"the":[10,23,31,72,79,86,141,144,155,158,165,169,173,178,191,214,221],"past":[11],"decades":[12],"have":[13,35,203],"witnessed":[14],"large":[15],"amount":[16],"of":[17,25,194,225,231],"successful":[18],"breakthroughs":[19],"applications":[21],"in":[22,47,143],"field":[24],"intelligent":[26,73],"fault":[27,39,75,88,128,229],"diagnosis":[28,230],"(IFD).":[29],"However,":[30],"historical":[32],"IFD":[33],"methods":[34],"difficulties":[36],"for":[37,49,93,125,227],"compound":[38,74,87,228],"diagnosis,":[40,76],"when":[41],"labeled":[42],"data":[43,180],"cannot":[44],"be":[45,100],"collected":[46,181],"advance":[48],"new":[50,197],"or":[51],"extreme":[52],"working":[53,104,184,198],"conditions.":[54,199],"Facing":[55],"with":[56,220],"such":[57],"challenges,":[58],"a":[59,110,148],"deep":[60],"adversarial":[61,136],"capsule":[62],"network":[63],"(DACN)":[64],"is":[65,123,138,175],"proposed":[66],"to":[67,106,167,189],"embed":[68],"multidomain":[69,120,132,234],"generalization":[70,235],"into":[71,89,140],"so":[77],"that":[78,152,213],"DACN":[80,111,142,166,174,215],"not":[81],"only":[82],"can":[83,99,153,163],"intelligently":[84],"decouple":[85],"multiple":[90,183],"single":[91],"faults":[92],"industrial":[94],"equipment":[95],"(IE)":[96],"but":[97],"also":[98],"generalized":[101],"from":[102],"certain":[103],"conditions":[105],"another":[107],"new.":[108],"First,":[109],"including":[112],"feature":[113,126],"extractor":[114],"(FE),":[115],"decoupling":[116],"classifier":[117,121],"(DC)":[118],"(MC)":[122],"constructed":[124],"learning,":[127],"decoupling,":[129],"unsupervised":[131],"adaptation,":[133],"respectively.":[134],"Second,":[135],"training":[137,145],"introduced":[139],"stage":[146],"via":[147],"gradient":[149],"reversal":[150],"layer":[151],"build":[154],"connection":[156],"between":[157],"FE":[159],"MC,":[161],"which":[162,211],"force":[164],"learn":[168],"domain-invariance":[170],"features.":[171],"Finally,":[172],"trained":[176],"using":[177],"single-fault":[179],"under":[182,196,233],"conditions,":[185],"then":[187],"applied":[188],"monitor":[190],"health":[192],"condition":[193],"IE":[195,232],"The":[200],"cross-validation":[201],"experiments":[202],"been":[204],"implemented":[205],"on":[206],"an":[207,217],"automobile":[208],"transmission":[209],"(AT),":[210],"illustrates":[212],"obtains":[216],"optimum":[218],"performance":[219],"highest":[222],"average":[223],"accuracy":[224],"97.65%":[226],"task":[236],"outperforms":[238],"other":[239],"related":[240],"methods.":[241]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":63},{"year":2024,"cited_by_count":66},{"year":2023,"cited_by_count":43},{"year":2022,"cited_by_count":25},{"year":2021,"cited_by_count":11}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}