{"id":"https://openalex.org/W3084404279","doi":"https://doi.org/10.1109/access.2020.3022840","title":"A Generic Intelligent Bearing Fault Diagnosis System Using Convolutional Neural Networks With Transfer Learning","display_name":"A Generic Intelligent Bearing Fault Diagnosis System Using Convolutional Neural Networks With Transfer Learning","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3084404279","doi":"https://doi.org/10.1109/access.2020.3022840","mag":"3084404279"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3022840","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3022840","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09187800.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/ielx7/6287639/8948470/09187800.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089404454","display_name":"Tao L\u00fc","orcid":"https://orcid.org/0000-0001-8117-2012"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Lu","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011845571","display_name":"Fanqianhui Yu","orcid":"https://orcid.org/0000-0001-9670-5950"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fanqianhui Yu","raw_affiliation_strings":["College of Food Science and Engineering, Ocean University of China, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Food Science and Engineering, Ocean University of China, Qingdao, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011132626","display_name":"Baokun Han","orcid":"https://orcid.org/0000-0001-7367-6253"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baokun Han","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027947686","display_name":"Jinrui Wang","orcid":"https://orcid.org/0000-0001-8690-0672"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinrui Wang","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5089404454"],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.7481,"has_fulltext":true,"cited_by_count":58,"citation_normalized_percentile":{"value":0.9547156,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"164807","last_page":"164814"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9593999981880188,"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":0.9340000152587891,"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/computer-science","display_name":"Computer science","score":0.8245339393615723},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7959879636764526},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.7017903327941895},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6798050999641418},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6464167833328247},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6420968174934387},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.6343700885772705},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5487103462219238},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5181697607040405},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46365460753440857},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45470625162124634},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4539106786251068},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4522444009780884},{"id":"https://openalex.org/keywords/fault-simulator","display_name":"Fault Simulator","score":0.4509834051132202},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4392904043197632},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.43580561876296997},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3441796898841858},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.23680979013442993},{"id":"https://openalex.org/keywords/actuator","display_name":"Actuator","score":0.10957971215248108}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8245339393615723},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7959879636764526},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.7017903327941895},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6798050999641418},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6464167833328247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6420968174934387},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.6343700885772705},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5487103462219238},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5181697607040405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46365460753440857},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45470625162124634},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4539106786251068},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4522444009780884},{"id":"https://openalex.org/C2776365744","wikidata":"https://www.wikidata.org/wiki/Q5438149","display_name":"Fault Simulator","level":5,"score":0.4509834051132202},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4392904043197632},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.43580561876296997},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3441796898841858},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.23680979013442993},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.10957971215248108},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C13625343","wikidata":"https://www.wikidata.org/wiki/Q7627418","display_name":"Stuck-at fault","level":4,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3022840","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3022840","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09187800.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:6ac1d372e294429bbc454e5daec878b5","is_oa":true,"landing_page_url":"https://doaj.org/article/6ac1d372e294429bbc454e5daec878b5","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"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 8, Pp 164807-164814 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3022840","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3022840","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09187800.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":[],"awards":[{"id":"https://openalex.org/G637440373","display_name":null,"funder_award_id":"201808370191","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G8589651859","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G8635980279","display_name":null,"funder_award_id":"201806330047","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320308354","display_name":"Acoustical Society of America","ror":"https://ror.org/049e4we54"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3084404279.pdf","grobid_xml":"https://content.openalex.org/works/W3084404279.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W243674440","https://openalex.org/W1675477313","https://openalex.org/W1978201669","https://openalex.org/W2019505419","https://openalex.org/W2064323378","https://openalex.org/W2108598243","https://openalex.org/W2148143831","https://openalex.org/W2163605009","https://openalex.org/W2195459533","https://openalex.org/W2219903032","https://openalex.org/W2295427627","https://openalex.org/W2404692435","https://openalex.org/W2480364715","https://openalex.org/W2485614840","https://openalex.org/W2581853886","https://openalex.org/W2584994008","https://openalex.org/W2591591405","https://openalex.org/W2744043610","https://openalex.org/W2744790985","https://openalex.org/W2787065855","https://openalex.org/W2792191775","https://openalex.org/W2804879845","https://openalex.org/W2898375427","https://openalex.org/W2898597600","https://openalex.org/W2898760173","https://openalex.org/W2901051598","https://openalex.org/W2902985761","https://openalex.org/W2910121883","https://openalex.org/W2910881901","https://openalex.org/W2912412749","https://openalex.org/W2940589124","https://openalex.org/W2974140502","https://openalex.org/W2979865603","https://openalex.org/W2990705538","https://openalex.org/W2995279030","https://openalex.org/W2995758361","https://openalex.org/W3009933106","https://openalex.org/W3037346518","https://openalex.org/W3100321043","https://openalex.org/W4229494842","https://openalex.org/W4246432115","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4390929683","https://openalex.org/W2317564947"],"abstract_inverted_index":{"It":[0],"is":[1,24,207],"very":[2],"important":[3],"and":[4,12,30,55,79,119,122,130,174,181,216],"necessary":[5],"to":[6,27,52,64,92,104],"diagnose":[7],"bearing":[8,40,58,72,90,158,214],"faults":[9,73,215],"timely,":[10],"quickly,":[11],"accurately":[13],"in":[14,167,221],"practical":[15,222],"applications,":[16],"because":[17],"the":[18,22,28,33,84,94,97,107,128,140,148,153,171,182,200,204],"operation":[19],"status":[20],"of":[21,32,68,96,133,135,156,184],"bearings":[23],"directly":[25],"related":[26],"performance":[29,95],"reliability":[31],"rotating":[34],"machinery.":[35],"Therefore,":[36],"a":[37,218],"generic":[38],"intelligent":[39],"fault":[41],"diagnosis":[42],"system":[43],"based":[44],"on":[45],"AlexNet":[46],"with":[47,113],"transfer":[48],"learning":[49,61],"was":[50,62,189],"proposed":[51,98,108,205],"automatically":[53],"identify":[54],"classify":[56],"different":[57,76,213],"faults.":[59],"Transfer":[60],"used":[63,186,195],"avoid":[65],"overfitting":[66],"problem":[67],"deep":[69],"network.":[70],"Five":[71],"at":[74],"two":[75,163],"motor":[77],"loads":[78],"speeds":[80],"were":[81,162,178],"selected":[82],"from":[83],"Case":[85],"Western":[86],"Reserve":[87],"University":[88],"(CWRU)":[89],"dataset":[91,173,176],"validate":[93],"method.":[99],"Results":[100],"showed":[101],"that":[102,203],"compared":[103],"previous":[105],"methods,":[106],"method":[109,206],"achieved":[110],"excellent":[111],"performance,":[112],"overall":[114],"classification":[115,142,149],"accuracy":[116],"over":[117],"99.7%,":[118],"fast":[120],"training":[121,172],"testing":[123,164,175,188],"times.":[124],"Feature":[125],"visualization":[126],"displayed":[127],"common":[129],"high-level":[131],"features":[132,155],"spectrograms":[134],"vibration":[136],"signals":[137],"learned":[138,152],"by":[139],"trained":[141],"model.":[143],"And":[144],"strongest":[145],"activations":[146],"demonstrated":[147],"model":[150],"had":[151],"correct":[154],"each":[157],"fault.":[159],"Importantly,":[160],"there":[161],"datasets":[165],"employed":[166],"this":[168],"study,":[169],"where":[170],"(2)":[177],"completely":[179],"independent":[180],"number":[183],"sub-spectrograms":[185],"for":[187,196,211],"3-5":[190],"times":[191],"greater":[192],"than":[193],"those":[194],"training.":[197],"Thus,":[198],"all":[199],"results":[201],"suggest":[202],"stable,":[208],"reliable,":[209],"suitable":[210],"diagnosing":[212],"has":[217],"great":[219],"potential":[220],"applications.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":6}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}