{"id":"https://openalex.org/W2991614907","doi":"https://doi.org/10.1145/3366194.3366276","title":"Fault Diagnosis Method of Mechanical Equipment Based on Convolutional Neural Network","display_name":"Fault Diagnosis Method of Mechanical Equipment Based on Convolutional Neural Network","publication_year":2019,"publication_date":"2019-09-20","ids":{"openalex":"https://openalex.org/W2991614907","doi":"https://doi.org/10.1145/3366194.3366276","mag":"2991614907"},"language":"en","primary_location":{"id":"doi:10.1145/3366194.3366276","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3366194.3366276","pdf_url":null,"source":{"id":"https://openalex.org/S4306523677","display_name":"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence","raw_type":"proceedings-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/A5101917144","display_name":"Jun Zhou","orcid":"https://orcid.org/0000-0001-9352-9584"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["Department of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai China"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100751238","display_name":"Wenfeng Zhang","orcid":"https://orcid.org/0000-0001-9487-9375"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenfeng Zhang","raw_affiliation_strings":["Department of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai China"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004311779","display_name":"WeiZhao Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"WeiZhao Sun","raw_affiliation_strings":["Department of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai China"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai China","institution_ids":["https://openalex.org/I141962983"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101917144"],"corresponding_institution_ids":["https://openalex.org/I141962983"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.23816605,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"459","last_page":"465"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9907000064849854,"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":0.9907000064849854,"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":0.9829000234603882,"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/T13891","display_name":"Engineering Diagnostics and Reliability","score":0.9767000079154968,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/feature-extraction","display_name":"Feature extraction","score":0.7996781468391418},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7739928960800171},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7140903472900391},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.7038406133651733},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5999798774719238},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5720610022544861},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5578323602676392},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.552673876285553},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5468525290489197},{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"Condition monitoring","score":0.5015161037445068},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49422720074653625},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4211884140968323},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4183991551399231},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2385595440864563},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.20345550775527954},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.08689510822296143}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7996781468391418},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7739928960800171},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7140903472900391},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.7038406133651733},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5999798774719238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5720610022544861},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5578323602676392},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.552673876285553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5468525290489197},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.5015161037445068},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49422720074653625},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4211884140968323},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4183991551399231},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2385595440864563},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.20345550775527954},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.08689510822296143},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3366194.3366276","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3366194.3366276","pdf_url":null,"source":{"id":"https://openalex.org/S4306523677","display_name":"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1980005417","https://openalex.org/W2013124207","https://openalex.org/W2058514560","https://openalex.org/W2092777731","https://openalex.org/W2095307887","https://openalex.org/W2100495367","https://openalex.org/W2112796928","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2219903032","https://openalex.org/W2274246713","https://openalex.org/W2285341434","https://openalex.org/W2393767269","https://openalex.org/W2480364715","https://openalex.org/W2744686084","https://openalex.org/W2919115771"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Mechanical":[0],"equipment":[1,17,80],"is":[2,20,81,96,153],"becoming":[3],"much":[4,28],"larger,":[5],"more":[6,9,29],"precise":[7],"and":[8,32,56,59,87,108,143],"autonomous":[10],"in":[11,78],"current":[12],"industrial":[13],"society.":[14],"The":[15,146],"mechanical":[16,67,79],"fault":[18,140,144,161],"detection":[19],"entering":[21],"the":[22,64,84,101,105,110,115,121,124,128,150,164,173],"age":[23],"of":[24,52,66,123,133],"'big":[25,68],"data'":[26],"for":[27],"monitoring":[30,106],"points":[31],"sampling":[33],"rate.":[34],"Traditional":[35],"diagnosis":[36,89],"methods":[37],"based":[38,91],"on":[39,92],"\"signal":[40],"processing":[41,54],"feature":[42,130,141],"extraction":[43,131,142],"+":[44],"machine":[45],"learning":[46],"classification\"":[47],"require":[48],"a":[49,88],"large":[50],"amount":[51],"signal":[53,103,107,117],"technology":[55],"diagnostic":[57],"experience":[58],"can":[60,137],"no":[61],"longer":[62],"meet":[63],"requirements":[65],"data'.":[69],"To":[70],"solve":[71],"this":[72],"problem,":[73],"an":[74],"important":[75],"part":[76],"bearing":[77],"taken":[82],"as":[83,104,120],"research":[85],"object,":[86],"method":[90,99,152],"convolutional":[93,134],"neural":[94,135],"network":[95,136],"proposed.":[97],"This":[98],"uses":[100,109],"vibration":[102,116],"Fourier":[111],"transform":[112],"to":[113,155],"generate":[114],"spectrum":[118],"picture":[119],"input":[122],"whole":[125],"system.":[126],"Using":[127],"powerful":[129],"capability":[132],"automatically":[138],"complete":[139],"identification.":[145],"results":[147],"show":[148],"that":[149],"proposed":[151],"able":[154],"not":[156],"only":[157],"adaptively":[158],"mine":[159],"available":[160],"characteristics":[162],"from":[163],"data,":[165],"but":[166],"also":[167],"obtain":[168],"higher":[169],"identification":[170],"accuracy":[171],"than":[172],"existing":[174],"methods.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
