{"id":"https://openalex.org/W3126635901","doi":"https://doi.org/10.1109/access.2021.3056767","title":"Fault Diagnosis of Bearings Based on Multi-Sensor Information Fusion and 2D Convolutional Neural Network","display_name":"Fault Diagnosis of Bearings Based on Multi-Sensor Information Fusion and 2D Convolutional Neural Network","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3126635901","doi":"https://doi.org/10.1109/access.2021.3056767","mag":"3126635901"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3056767","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3056767","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09345801.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09345801.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100717646","display_name":"Jiaxing Wang","orcid":"https://orcid.org/0000-0002-1296-1621"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxing Wang","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100740238","display_name":"Dazhi Wang","orcid":"https://orcid.org/0000-0001-8067-9313"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dazhi Wang","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0001-8067-9313","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054023521","display_name":"Sihan Wang","orcid":"https://orcid.org/0000-0001-6459-4678"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sihan Wang","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100339854","display_name":"Wenhui Li","orcid":"https://orcid.org/0000-0002-0385-2132"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhui Li","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-0385-2132","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114127077","display_name":"Keling Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Keling Song","raw_affiliation_strings":["China North Vehicle Research Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China North Vehicle Research Institute, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":11.5252,"has_fulltext":true,"cited_by_count":120,"citation_normalized_percentile":{"value":0.99043286,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"9","issue":null,"first_page":"23717","last_page":"23725"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9980999827384949,"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":0.9980999827384949,"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":0.9890999794006348,"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"}},{"id":"https://openalex.org/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.9879000186920166,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.810305118560791},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.746329665184021},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6219387650489807},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5720406770706177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5290896892547607},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.524222731590271},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5158376097679138},{"id":"https://openalex.org/keywords/information-fusion","display_name":"Information fusion","score":0.5100036859512329},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4367428719997406},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09062963724136353}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.810305118560791},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.746329665184021},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6219387650489807},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5720406770706177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5290896892547607},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.524222731590271},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5158376097679138},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.5100036859512329},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4367428719997406},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09062963724136353},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3056767","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3056767","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09345801.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ee0632c2b1584057bc54eb986e3ee610","is_oa":true,"landing_page_url":"https://doaj.org/article/ee0632c2b1584057bc54eb986e3ee610","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 23717-23725 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3056767","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3056767","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09345801.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6399999856948853}],"awards":[{"id":"https://openalex.org/G5992644727","display_name":null,"funder_award_id":"52077027","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":30,"referenced_works":["https://openalex.org/W2103692342","https://openalex.org/W2140336071","https://openalex.org/W2141188346","https://openalex.org/W2161645812","https://openalex.org/W2166749505","https://openalex.org/W2296077894","https://openalex.org/W2404692435","https://openalex.org/W2480364715","https://openalex.org/W2556013418","https://openalex.org/W2593479727","https://openalex.org/W2603304445","https://openalex.org/W2765226309","https://openalex.org/W2768753204","https://openalex.org/W2782742812","https://openalex.org/W2782766333","https://openalex.org/W2792191775","https://openalex.org/W2886471976","https://openalex.org/W2889052685","https://openalex.org/W2895063750","https://openalex.org/W2897680073","https://openalex.org/W2897735448","https://openalex.org/W2939978363","https://openalex.org/W2945870846","https://openalex.org/W2970341933","https://openalex.org/W2971479067","https://openalex.org/W3022604663","https://openalex.org/W3083904687","https://openalex.org/W4214632657","https://openalex.org/W6782779458","https://openalex.org/W6808868985"],"related_works":["https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2152662039","https://openalex.org/W79444681","https://openalex.org/W2956133731","https://openalex.org/W2383241417","https://openalex.org/W2018887750","https://openalex.org/W3088112989","https://openalex.org/W2355249486"],"abstract_inverted_index":{"Intelligent":[0],"operation":[1],"and":[2,52,63,71,78,134,164,179,189,200],"maintenance":[3],"is":[4,45,110,147],"an":[5,137],"important":[6],"part":[7],"of":[8,17,25,34,39,61,68,97,123,159,176],"Industry":[9],"4.0.":[10],"In":[11,90],"order":[12],"to":[13,29,86,112,141],"realize":[14,142],"the":[15,31,35,57,66,87,95,119,150,157,165,184,194],"intelligent":[16],"plant":[18,58],"equipment,":[19],"it":[20],"will":[21],"make":[22],"full":[23],"use":[24],"artificial":[26],"intelligence":[27],"methods":[28],"evaluate":[30],"operating":[32],"status":[33],"equipment.":[36],"Fault":[37],"diagnosis":[38],"industrial":[40],"equipment":[41],"represented":[42],"by":[43],"bearings":[44],"critical":[46],"in":[47,102],"smart":[48],"manufacturing.":[49],"Early,":[50],"online":[51],"accurate":[53],"diagnostics":[54],"can":[55,196],"save":[56],"a":[59,84,104,130],"lot":[60],"time":[62],"expense.":[64],"With":[65],"development":[67],"sensor":[69],"technology":[70],"deep":[72],"learning":[73],"technology,":[74],"multi-sensor":[75,106],"information":[76,107],"fusion":[77,108],"convolutional":[79],"neural":[80],"network":[81],"(CNN)":[82],"provide":[83],"solution":[85],"above":[88],"problems.":[89],"this":[91],"paper,":[92],"based":[93],"on":[94,149],"characteristics":[96],"mechanical":[98],"vibration":[99,121],"signal":[100,143],"propagation":[101],"space,":[103],"new":[105],"method":[109,117,146],"proposed":[111],"implement":[113],"fault":[114,170,191,205],"classification.":[115,144],"This":[116],"constructs":[118],"time-domain":[120],"signals":[122],"multiple":[124],"sensors":[125],"from":[126],"different":[127],"position":[128],"into":[129],"rectangular":[131],"two-dimensional":[132],"matrix,":[133],"then":[135],"uses":[136],"improved":[138],"2D":[139,187],"CNN":[140,188],"The":[145],"validated":[148],"open":[151],"dataset":[152,166],"Case":[153],"Western":[154],"Reserve":[155],"University,":[156],"University":[158],"Cincinnati":[160],"IMS":[161],"bearing":[162,169],"database":[163],"form":[167],"designed":[168],"test":[171],"rig,":[172],"has":[173],"achieved":[174],"prediction":[175,206],"99.92%,":[177],"99.68%,":[178],"99.25%":[180],"respectively.":[181],"Compared":[182],"with":[183],"traditional":[185],"1D,":[186],"other":[190],"classification":[192],"methods,":[193],"model":[195],"utilize":[197],"less":[198],"data":[199],"computational":[201],"complexity,":[202],"achieve":[203],"higher":[204],"accuracy.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":32},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":8}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}