{"id":"https://openalex.org/W2998830408","doi":"https://doi.org/10.1109/tii.2020.2964117","title":"A Robust Weight-Shared Capsule Network for Intelligent Machinery Fault Diagnosis","display_name":"A Robust Weight-Shared Capsule Network for Intelligent Machinery Fault Diagnosis","publication_year":2020,"publication_date":"2020-01-07","ids":{"openalex":"https://openalex.org/W2998830408","doi":"https://doi.org/10.1109/tii.2020.2964117","mag":"2998830408"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2020.2964117","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2020.2964117","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/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/A5100692407","display_name":"Shuhua Wang","orcid":"https://orcid.org/0000-0002-8825-8027"},"institutions":[{"id":"https://openalex.org/I4210093205","display_name":"Foxconn (China)","ror":"https://ror.org/00jb92367","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210093205","https://openalex.org/I4210108919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhua Wang","raw_affiliation_strings":["Foxconn Industrial Internet Company, Ltd, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Foxconn Industrial Internet Company, Ltd, Shenzhen, China","institution_ids":["https://openalex.org/I4210093205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393104","display_name":"Guanghui Li","orcid":"https://orcid.org/0000-0001-8835-8346"},"institutions":[{"id":"https://openalex.org/I4210093205","display_name":"Foxconn (China)","ror":"https://ror.org/00jb92367","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210093205","https://openalex.org/I4210108919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanghui Li","raw_affiliation_strings":["Foxconn Industrial Internet Company, Ltd, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Foxconn Industrial Internet Company, Ltd, Shenzhen, China","institution_ids":["https://openalex.org/I4210093205"]}]},{"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":5,"corresponding_author_ids":["https://openalex.org/A5082065343"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":11.1565,"has_fulltext":false,"cited_by_count":118,"citation_normalized_percentile":{"value":0.98947892,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"16","issue":"10","first_page":"6466","last_page":"6475"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9980000257492065,"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":0.9980000257492065,"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/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.9445000290870667,"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/T13324","display_name":"Scientific and Engineering Research Topics","score":0.9326000213623047,"subfield":{"id":"https://openalex.org/subfields/3506","display_name":"Periodontics"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7715960144996643},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6652459502220154},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.626784086227417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5886847972869873},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.570440948009491},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.48797720670700073},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4796655476093292},{"id":"https://openalex.org/keywords/weight-function","display_name":"Weight function","score":0.4746283292770386},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47157496213912964},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43734118342399597},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37139731645584106},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3450416922569275},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20125600695610046},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14178466796875}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7715960144996643},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6652459502220154},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.626784086227417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5886847972869873},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.570440948009491},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48797720670700073},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4796655476093292},{"id":"https://openalex.org/C134466208","wikidata":"https://www.wikidata.org/wiki/Q1520657","display_name":"Weight function","level":2,"score":0.4746283292770386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47157496213912964},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43734118342399597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37139731645584106},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3450416922569275},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20125600695610046},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14178466796875},{"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},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2020.2964117","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2020.2964117","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":[{"display_name":"Reduced inequalities","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1002450208","display_name":null,"funder_award_id":"51475170","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G164778973","display_name":null,"funder_award_id":"2018YFB1702400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"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"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2163605009","https://openalex.org/W2187089797","https://openalex.org/W2210061839","https://openalex.org/W2219903032","https://openalex.org/W2287972354","https://openalex.org/W2562762876","https://openalex.org/W2584994008","https://openalex.org/W2591055632","https://openalex.org/W2601590138","https://openalex.org/W2603304445","https://openalex.org/W2609688418","https://openalex.org/W2618530766","https://openalex.org/W2731372149","https://openalex.org/W2744604411","https://openalex.org/W2747276445","https://openalex.org/W2763583057","https://openalex.org/W2773549135","https://openalex.org/W2783074568","https://openalex.org/W2784294927","https://openalex.org/W2789811186","https://openalex.org/W2794869810","https://openalex.org/W2802633978","https://openalex.org/W2809744928","https://openalex.org/W2810292802","https://openalex.org/W2848973885","https://openalex.org/W2887782657","https://openalex.org/W2893747136","https://openalex.org/W2899279252","https://openalex.org/W2899369559","https://openalex.org/W2899879087","https://openalex.org/W2900529838","https://openalex.org/W2904648439","https://openalex.org/W2905166565","https://openalex.org/W2907541186","https://openalex.org/W2907864265","https://openalex.org/W2908441554","https://openalex.org/W2911827809","https://openalex.org/W2916064970","https://openalex.org/W2919115771","https://openalex.org/W2939852233","https://openalex.org/W2942682738","https://openalex.org/W2946048316","https://openalex.org/W2948689530","https://openalex.org/W2963703618","https://openalex.org/W2964121744","https://openalex.org/W6631190155","https://openalex.org/W6733120587","https://openalex.org/W6743446608"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"In":[0,122],"practical":[1],"industrial":[2],"applications,":[3],"the":[4,15,21,27,98,120,133,137],"working":[5,28,66,145],"conditions":[6,146],"of":[7,23,62,136,149],"machinery":[8,63],"are":[9,94,116,128],"changing":[10],"with":[11,20],"long-term":[12],"operation,":[13],"and":[14],"health":[16],"status":[17],"is":[18,56,79],"declining":[19],"degradation":[22],"crucial":[24],"components.":[25],"When":[26],"condition":[29,39],"changes,":[30],"prior":[31],"diagnosis":[32,61,126],"models":[33],"cannot":[34],"be":[35],"generalized":[36],"from":[37],"one":[38],"to":[40,81,96,118,131],"another.":[41],"To":[42],"solve":[43],"this":[44,48,123],"challenging":[45],"issue,":[46],"in":[47],"article":[49],"a":[50],"robust":[51],"weight-shared":[52,92],"capsule":[53,87],"network":[54,78],"(WSCN)":[55],"introduced":[57],"for":[58,101],"intelligent":[59],"fault":[60,103],"under":[64,143],"varying":[65,144],"conditions.":[67],"First,":[68],"taking":[69],"raw":[70],"accelerometer":[71],"signals":[72],"as":[73,109,111],"inputs,":[74],"one-dimensional":[75],"convolutional":[76],"neural":[77],"constructed":[80],"extract":[82],"discriminative":[83],"characteristics.":[84],"Second,":[85],"various":[86],"layers":[88],"based":[89],"on":[90],"multistacked":[91],"capsules":[93],"developed":[95],"enhance":[97],"generalization":[99,134],"performance":[100,135],"further":[102],"classification.":[104],"Finally,":[105],"margin":[106],"loss":[107],"function":[108],"well":[110],"agreement-based":[112],"dynamic":[113],"routing":[114],"algorithm":[115],"employed":[117],"optimize":[119],"WSCN.":[121],"article,":[124],"two":[125],"cases":[127],"carried":[129],"out":[130],"demonstrate":[132],"WSCN":[138],"which":[139],"obtains":[140],"higher":[141],"accuracy":[142],"than":[147],"that":[148],"other":[150],"state-of-the-art":[151],"methods.":[152]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":30},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":8}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}