{"id":"https://openalex.org/W4206568770","doi":"https://doi.org/10.1109/tii.2021.3134273","title":"ConditionSenseNet: A Deep Interpolatory ConvNet for Bearing Intelligent Diagnosis Under Variational Working Conditions","display_name":"ConditionSenseNet: A Deep Interpolatory ConvNet for Bearing Intelligent Diagnosis Under Variational Working Conditions","publication_year":2021,"publication_date":"2021-12-13","ids":{"openalex":"https://openalex.org/W4206568770","doi":"https://doi.org/10.1109/tii.2021.3134273"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2021.3134273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2021.3134273","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/A5102838601","display_name":"Yinjun Wang","orcid":"https://orcid.org/0000-0001-6749-9203"},"institutions":[{"id":"https://openalex.org/I145581781","display_name":"Chongqing Technology and Business University","ror":"https://ror.org/05hqf1284","country_code":"CN","type":"education","lineage":["https://openalex.org/I145581781"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinjun Wang","raw_affiliation_strings":["School of Mechanical Engineering at Chongqing Technology and Business University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0001-6749-9203","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering at Chongqing Technology and Business University, Chongqing, China","institution_ids":["https://openalex.org/I145581781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034422878","display_name":"Xiaoxi Ding","orcid":"https://orcid.org/0000-0001-5321-0894"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxi Ding","raw_affiliation_strings":["State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0001-5321-0894","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101489436","display_name":"Rui Liu","orcid":"https://orcid.org/0000-0003-1642-3473"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Liu","raw_affiliation_strings":["State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069181198","display_name":"Yimin Shao","orcid":"https://orcid.org/0000-0002-2698-7005"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yimin Shao","raw_affiliation_strings":["State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-2698-7005","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.2401,"has_fulltext":false,"cited_by_count":59,"citation_normalized_percentile":{"value":0.95014466,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"18","issue":"10","first_page":"6558","last_page":"6568"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9873999953269958,"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/T10188","display_name":"Advanced machining processes and optimization","score":0.9545000195503235,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6807513236999512},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6463987231254578},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6089804172515869},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5954594612121582},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5850096940994263},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5264987349510193},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4704781174659729},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.46345728635787964},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4439391791820526},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4344756007194519},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3407282829284668}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6807513236999512},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6463987231254578},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6089804172515869},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5954594612121582},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5850096940994263},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5264987349510193},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4704781174659729},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.46345728635787964},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4439391791820526},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4344756007194519},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3407282829284668},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2021.3134273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2021.3134273","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":[{"score":0.4099999964237213,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G1733408855","display_name":null,"funder_award_id":"cstc2019jcyj-msxmX0346","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"},{"id":"https://openalex.org/G3491814942","display_name":null,"funder_award_id":"2020CDJGFCD002","funder_id":"https://openalex.org/F4320329878","funder_display_name":"Central University Basic Research Fund of China"},{"id":"https://openalex.org/G7041080164","display_name":null,"funder_award_id":"51805051","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/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329878","display_name":"Central University Basic Research Fund of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2112796928","https://openalex.org/W2156387975","https://openalex.org/W2194775991","https://openalex.org/W2471080557","https://openalex.org/W2584994008","https://openalex.org/W2595657631","https://openalex.org/W2778801251","https://openalex.org/W2783074568","https://openalex.org/W2794869810","https://openalex.org/W2802595313","https://openalex.org/W2804061829","https://openalex.org/W2804879845","https://openalex.org/W2893747136","https://openalex.org/W2900367617","https://openalex.org/W2914169887","https://openalex.org/W2973424371","https://openalex.org/W2994902374","https://openalex.org/W2998830408","https://openalex.org/W3000384844","https://openalex.org/W3010877614","https://openalex.org/W3034650994","https://openalex.org/W3042061366","https://openalex.org/W3089171422","https://openalex.org/W3106577699","https://openalex.org/W3128871194","https://openalex.org/W3156676812","https://openalex.org/W3156954244","https://openalex.org/W6682889407","https://openalex.org/W6783857909"],"related_works":["https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W4380075502","https://openalex.org/W3208266890","https://openalex.org/W4312417841","https://openalex.org/W2606416966"],"abstract_inverted_index":{"Deep":[0],"learning,":[1],"with":[2,67,83,162,209],"its":[3],"ability":[4],"of":[5,29,72,122,165,192,228,235],"feature":[6,134],"mining":[7],"and":[8,26,78,207,222],"logical":[9],"judgement,":[10],"has":[11,38],"been":[12,39],"widely":[13],"studied":[14],"in":[15,159,177],"industrial":[16],"intelligent":[17,199],"diagnosis,":[18],"including":[19],"bearing":[20,198],"fault":[21,99,133],"diagnosis.":[22],"However,":[23],"an":[24],"explicable":[25],"representable":[27],"expression":[28],"deep":[30,62,86,212],"learning":[31,213],"architecture":[32,66,148],"for":[33,197],"the":[34,84,91,94,98,106,120,155,160,163,170,190,193,216,226,233,245],"variational":[35,55,171,202],"working":[36,56,103,115,138,166,172,203,246],"conditions":[37,167],"rarely":[40],"discussed":[41],"while":[42,105],"it":[43],"is":[44,81,111,127,141,230,248],"known":[45],"that":[46],"vibration":[47],"features":[48,100,157],"from":[49,90,113],"bearings":[50],"are":[51,186],"seriously":[52],"influenced":[53],"by":[54,239],"conditions.":[57,204],"In":[58],"this":[59,178],"article,":[60],"a":[61,114,131,150],"interpolation":[63,123],"ConvNet":[64,87],"(DICN)":[65],"three":[68,183],"special":[69],"layers,":[70],"consisting":[71],"multiple":[73],"sub-ConvNet":[74,96],"units,":[75],"weight":[76,109],"unit,":[77,80],"fusion":[79,125],"presented":[82],"basic":[85],"architecture.":[88],"Different":[89],"traditional":[92],"network,":[93],"first":[95],"extracts":[97],"under":[101,136,201],"different":[102],"conditions,":[104],"corresponding":[107],"condition":[108,116,247],"unit":[110,126],"learned":[112],"identification":[117],"task.":[118],"With":[119],"principle":[121],"theory,":[124],"employed":[128],"to":[129,152,188],"achieve":[130],"sound":[132],"representation":[135],"unknown":[137],"condition,":[139],"which":[140],"named":[142],"as":[143],"ConditionSenseNet":[144],"(CSN).":[145],"This":[146],"CSN":[147],"provides":[149],"way":[151],"dynamically":[153],"express":[154],"crucial":[156],"hidden":[158],"samples":[161],"influence":[164],"suppressed,":[168],"especially":[169],"factors":[173],"will":[174],"be":[175],"interpolated":[176],"nonlinear":[179],"fitting":[180],"model.":[181],"Additionally,":[182],"experimental":[184],"studies":[185],"tested":[187],"verify":[189],"effectiveness":[191],"proposed":[194,217],"DICN":[195,229],"method":[196,218],"diagnosis":[200],"The":[205],"results":[206],"comparisons":[208],"other":[210],"seven":[211],"models":[214],"show":[215],"shows":[219],"outstanding":[220],"robustness":[221],"higher":[223,231],"accuracy":[224,227],"where":[225],"than":[232,241],"one":[234],"convolution":[236],"neural":[237],"network":[238],"more":[240],"9%":[242],"even":[243],"if":[244],"variational.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":8}],"updated_date":"2026-08-12T07:12:00.856984","created_date":"2025-10-10T00:00:00"}