{"id":"https://openalex.org/W3093842373","doi":"https://doi.org/10.1109/cacre50138.2020.9229954","title":"An Intelligent Fault Diagnosis Method of Rolling Bearing with Wide Convolution Kernel Network","display_name":"An Intelligent Fault Diagnosis Method of Rolling Bearing with Wide Convolution Kernel Network","publication_year":2020,"publication_date":"2020-09-01","ids":{"openalex":"https://openalex.org/W3093842373","doi":"https://doi.org/10.1109/cacre50138.2020.9229954","mag":"3093842373"},"language":"en","primary_location":{"id":"doi:10.1109/cacre50138.2020.9229954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cacre50138.2020.9229954","pdf_url":null,"source":{"id":"https://openalex.org/S4306498616","display_name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","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":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5033291022","display_name":"Chuan Xiang","orcid":"https://orcid.org/0000-0002-6873-927X"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuan Xiang","raw_affiliation_strings":["College of Marine Electrical Engineering, College of Dalian Maritime University, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Marine Electrical Engineering, College of Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049039408","display_name":"Zejun Ren","orcid":"https://orcid.org/0000-0001-8638-3900"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zejun Ren","raw_affiliation_strings":["College of Marine Electrical Engineering, College of Dalian Maritime University, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Marine Electrical Engineering, College of Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I43313876"],"apc_list":null,"apc_paid":null,"fwci":1.2354,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.76312123,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"620","last_page":"624"},"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":0.9943000078201294,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9932000041007996,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.939939022064209},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.8108299374580383},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.7717196941375732},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.671146035194397},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6668809652328491},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6604464054107666},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.6058849096298218},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.5726718902587891},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5007789134979248},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4878978431224823},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46548572182655334},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4440236985683441},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.28584831953048706},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2698138356208801},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.14966228604316711},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1436588168144226},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.0649060606956482}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.939939022064209},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.8108299374580383},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.7717196941375732},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.671146035194397},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6668809652328491},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6604464054107666},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.6058849096298218},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.5726718902587891},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5007789134979248},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4878978431224823},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46548572182655334},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4440236985683441},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28584831953048706},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2698138356208801},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.14966228604316711},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1436588168144226},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0649060606956482},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cacre50138.2020.9229954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cacre50138.2020.9229954","pdf_url":null,"source":{"id":"https://openalex.org/S4306498616","display_name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","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":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2030024491","https://openalex.org/W2219903032","https://openalex.org/W2608623198","https://openalex.org/W2767031373","https://openalex.org/W2900706455"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W4386858688","https://openalex.org/W3034421924","https://openalex.org/W2982536526","https://openalex.org/W4380302312","https://openalex.org/W4385338604","https://openalex.org/W2949189996","https://openalex.org/W3008689640","https://openalex.org/W3081626085"],"abstract_inverted_index":{"In":[0],"this":[1,69],"paper,":[2],"a":[3],"method":[4,70],"based":[5],"on":[6],"two":[7],"wide":[8],"convolution":[9],"kernels":[10],"network":[11,32],"(WCNN)":[12],"is":[13],"proposed":[14],"for":[15],"the":[16,23,37,52,56,81],"fault":[17,58,77],"diagnosis":[18],"of":[19,26,40,76],"rolling":[20],"bearing.":[21],"Firstly,":[22],"vibration":[24,41],"signal":[25,42],"bearing":[27,57],"was":[28,49,59],"input":[29],"into":[30],"WCNN":[31],"which":[33],"acquired":[34],"and":[35,95],"extracted":[36],"intrinsic":[38],"features":[39],"by":[43,51,61],"itself.":[44],"The":[45],"whole":[46],"training":[47,98],"process":[48],"optimized":[50],"Adam":[53],"algorithm.":[54],"Finally,":[55],"diagnosed":[60],"softmax":[62],"function.":[63],"Compared":[64],"with":[65,96],"other":[66],"common":[67],"methods,":[68],"does":[71],"not":[72],"require":[73],"manual":[74],"extraction":[75],"features.":[78],"And":[79],"at":[80],"same":[82],"time,":[83],"average":[84],"diagnostic":[85],"accuracy":[86],"can":[87],"be":[88],"above":[89],"99%":[90],"in":[91],"different":[92],"noisy":[93],"environment":[94],"less":[97],"time.":[99]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
