{"id":"https://openalex.org/W4388263211","doi":"https://doi.org/10.3390/s23218703","title":"Enhanced Feature Extraction Network Based on Acoustic Signal Feature Learning for Bearing Fault Diagnosis","display_name":"Enhanced Feature Extraction Network Based on Acoustic Signal Feature Learning for Bearing Fault Diagnosis","publication_year":2023,"publication_date":"2023-10-25","ids":{"openalex":"https://openalex.org/W4388263211","doi":"https://doi.org/10.3390/s23218703","pmid":"https://pubmed.ncbi.nlm.nih.gov/37960402"},"language":"en","primary_location":{"id":"doi:10.3390/s23218703","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23218703","pdf_url":"https://www.mdpi.com/1424-8220/23/21/8703/pdf?version=1698226180","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/21/8703/pdf?version=1698226180","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017047898","display_name":"Yuanqing Luo","orcid":"https://orcid.org/0000-0002-4232-309X"},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanqing Luo","raw_affiliation_strings":["School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang 110870, China"],"affiliations":[{"raw_affiliation_string":"School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang 110870, China","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113038146","display_name":"Wenxia Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxia Lu","raw_affiliation_strings":["School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang 110870, China"],"affiliations":[{"raw_affiliation_string":"School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang 110870, China","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087051120","display_name":"Shuang Kang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103627","display_name":"BaiCheng Normal University","ror":"https://ror.org/01djkf495","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210103627"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuang Kang","raw_affiliation_strings":["School of Mechanical and Control Engineering, Baicheng Normal University, Baicheng 137000, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Control Engineering, Baicheng Normal University, Baicheng 137000, China","institution_ids":["https://openalex.org/I4210103627"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010129307","display_name":"Xueyong Tian","orcid":"https://orcid.org/0009-0003-3818-4853"},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueyong Tian","raw_affiliation_strings":["School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang 110870, China"],"affiliations":[{"raw_affiliation_string":"School of Environmental and Chemical Engineering, Shenyang University of Technology, Shenyang 110870, China","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076776445","display_name":"Xiaoqi Kang","orcid":null},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqi Kang","raw_affiliation_strings":["School of Mechanical Engineering, Shenyang University of Technology, Shenyang 110870, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shenyang University of Technology, Shenyang 110870, China","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100651291","display_name":"Feng Sun","orcid":"https://orcid.org/0000-0003-1355-2069"},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Sun","raw_affiliation_strings":["School of Mechanical Engineering, Shenyang University of Technology, Shenyang 110870, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shenyang University of Technology, Shenyang 110870, China","institution_ids":["https://openalex.org/I157507598"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5087051120"],"corresponding_institution_ids":["https://openalex.org/I4210103627"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":3.0854,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.91877177,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"23","issue":"21","first_page":"8703","last_page":"8703"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9840999841690063,"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":0.91839998960495,"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/feature-extraction","display_name":"Feature extraction","score":0.6698949933052063},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.638943076133728},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.598850429058075},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5858646631240845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5656277537345886},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5643484592437744},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5372689962387085},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5158397555351257},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5013408660888672},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.49613937735557556},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.42592722177505493},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4241287410259247},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4190003275871277},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12567880749702454}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6698949933052063},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.638943076133728},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.598850429058075},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5858646631240845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5656277537345886},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5643484592437744},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5372689962387085},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5158397555351257},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5013408660888672},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.49613937735557556},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.42592722177505493},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4241287410259247},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4190003275871277},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12567880749702454},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s23218703","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23218703","pdf_url":"https://www.mdpi.com/1424-8220/23/21/8703/pdf?version=1698226180","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:37960402","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37960402","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10647236","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10647236","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10647236/pdf/sensors-23-08703.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:fbcaf3e314ab4d339b9b495d7224fb29","is_oa":true,"landing_page_url":"https://doaj.org/article/fbcaf3e314ab4d339b9b495d7224fb29","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 23, Iss 21, p 8703 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s23218703","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23218703","pdf_url":"https://www.mdpi.com/1424-8220/23/21/8703/pdf?version=1698226180","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1171814716","display_name":null,"funder_award_id":"51675350","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7911316452","display_name":null,"funder_award_id":"2021JH1/10400031","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/F4320328772","display_name":"Shenyang Jianzhu University","ror":"https://ror.org/01zr73v18"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4388263211.pdf"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W2514268906","https://openalex.org/W2548698341","https://openalex.org/W2768753204","https://openalex.org/W2887507616","https://openalex.org/W2895876294","https://openalex.org/W2981982720","https://openalex.org/W2999516673","https://openalex.org/W3006944565","https://openalex.org/W3044539520","https://openalex.org/W3090238656","https://openalex.org/W3090682168","https://openalex.org/W3094346685","https://openalex.org/W3094882317","https://openalex.org/W3097068663","https://openalex.org/W3120907440","https://openalex.org/W3131848660","https://openalex.org/W3141784598","https://openalex.org/W3156676812","https://openalex.org/W3215145458","https://openalex.org/W4200039664","https://openalex.org/W4220669622","https://openalex.org/W4220702876","https://openalex.org/W4221103614","https://openalex.org/W4281644982","https://openalex.org/W4295956768","https://openalex.org/W4315815611","https://openalex.org/W4382281483"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2397288865","https://openalex.org/W4313906399","https://openalex.org/W4321487865","https://openalex.org/W2368524271","https://openalex.org/W4247116873","https://openalex.org/W2811106690","https://openalex.org/W2095030957","https://openalex.org/W2066827917","https://openalex.org/W2884201223"],"abstract_inverted_index":{"The":[0,42,168],"method":[1,170],"of":[2,33,141,174,181,186,205],"acoustic":[3,38,75,166],"radiation":[4],"signal":[5,39,76],"detection":[6],"not":[7],"only":[8,206],"enables":[9],"contactless":[10],"measurement":[11],"but":[12],"also":[13],"provides":[14],"comprehensive":[15],"state":[16],"information":[17,54,103],"during":[18],"equipment":[19],"operation.":[20],"This":[21],"paper":[22],"proposes":[23],"an":[24,172],"enhanced":[25],"feature":[26,40,55,102],"extraction":[27],"network":[28,44,69,131,151],"(EFEN)":[29],"for":[30,138],"fault":[31,111,133,156],"diagnosis":[32,134,157],"rolling":[34,142,161],"bearings":[35],"based":[36,164],"on":[37,165],"learning.":[41],"EFEN":[43,150],"comprises":[45],"four":[46],"main":[47],"components:":[48],"the":[49,53,59,66,73,128,149,189,214],"data":[50,95],"preprocessing":[51],"module,":[52],"selection":[56],"module":[57,63,70,118,135],"(IFSM),":[58],"channel":[60,115],"attention":[61,116],"mechanism":[62,117],"(CAMM),":[64],"and":[65,96,98,158,220],"convolutional":[67,129],"neural":[68,130],"(CNNM).":[71],"Firstly,":[72],"one-dimensional":[74],"is":[77,119,136],"transformed":[78],"into":[79],"a":[80,114,199],"two-dimensional":[81],"grayscale":[82],"image.":[83],"Then,":[84],"IFSM":[85],"utilizes":[86],"three":[87],"different-sized":[88],"convolution":[89],"filters":[90],"to":[91,101,121,124],"process":[92],"input":[93],"image":[94],"fuse":[97],"assign":[99,122],"weights":[100,123],"that":[104,148,213],"can":[105],"attenuate":[106],"noise":[107],"while":[108],"highlighting":[109],"effective":[110],"information.":[112],"Next,":[113],"introduced":[120],"each":[125],"channel.":[126],"Finally,":[127],"(CNN)":[132],"employed":[137],"accurate":[139],"classification":[140],"bearing":[143,162],"faults.":[144],"Experimental":[145],"results":[146],"demonstrate":[147],"achieves":[152,171],"high":[153,194],"accuracy":[154,173,191,219],"in":[155,179],"effectively":[159],"detects":[160],"faults":[163],"signals.":[167],"proposed":[169,215],"98.52%,":[175],"surpassing":[176],"other":[177],"methods":[178],"terms":[180],"performance.":[182],"In":[183],"comparative":[184,210],"analysis":[185,211],"antinoise":[187],"experiments,":[188],"average":[190,202],"remains":[192],"remarkably":[193],"at":[195],"96.62%,":[196],"accompanied":[197],"by":[198],"significantly":[200],"reduced":[201],"iteration":[203],"time":[204],"0.25":[207],"s.":[208],"Furthermore,":[209],"confirms":[212],"algorithm":[216],"exhibits":[217],"excellent":[218],"resistance":[221],"against":[222],"noise.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":6}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}