{"id":"https://openalex.org/W7118809633","doi":"https://doi.org/10.1109/indin64977.2025.11279497","title":"Research on Bearing Fault Diagnosis Based on IWOA-CNNLSTM","display_name":"Research on Bearing Fault Diagnosis Based on IWOA-CNNLSTM","publication_year":2025,"publication_date":"2025-07-12","ids":{"openalex":"https://openalex.org/W7118809633","doi":"https://doi.org/10.1109/indin64977.2025.11279497"},"language":null,"primary_location":{"id":"doi:10.1109/indin64977.2025.11279497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin64977.2025.11279497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 23rd International Conference on Industrial Informatics (INDIN)","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/A5122035571","display_name":"Chaoqun Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094602","display_name":"Tobacco Research Institute","ror":"https://ror.org/0099xbw16","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094602","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chaoqun Zheng","raw_affiliation_strings":["Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China","institution_ids":["https://openalex.org/I4210094602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110618934","display_name":"Di Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094602","display_name":"Tobacco Research Institute","ror":"https://ror.org/0099xbw16","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094602","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Wang","raw_affiliation_strings":["Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China","institution_ids":["https://openalex.org/I4210094602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085010059","display_name":"Weihua Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094602","display_name":"Tobacco Research Institute","ror":"https://ror.org/0099xbw16","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094602","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Feng","raw_affiliation_strings":["Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China","institution_ids":["https://openalex.org/I4210094602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089773731","display_name":"Yongsheng Wang","orcid":"https://orcid.org/0000-0002-9943-3687"},"institutions":[{"id":"https://openalex.org/I4210094602","display_name":"Tobacco Research Institute","ror":"https://ror.org/0099xbw16","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094602","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongsheng Wang","raw_affiliation_strings":["Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China","institution_ids":["https://openalex.org/I4210094602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122214281","display_name":"Guohao Zong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094602","display_name":"Tobacco Research Institute","ror":"https://ror.org/0099xbw16","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094602","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guohao Zong","raw_affiliation_strings":["Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China","institution_ids":["https://openalex.org/I4210094602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021730674","display_name":"Chenhao Cui","orcid":"https://orcid.org/0009-0006-5774-3579"},"institutions":[{"id":"https://openalex.org/I4210094602","display_name":"Tobacco Research Institute","ror":"https://ror.org/0099xbw16","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094602","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenhao Cui","raw_affiliation_strings":["Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou Tobacco Research Institute of CNTC,Zhengzhou,China","institution_ids":["https://openalex.org/I4210094602"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5122035571"],"corresponding_institution_ids":["https://openalex.org/I4210094602"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64495801,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.8306999802589417,"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":0.8306999802589417,"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/T12676","display_name":"Machine Learning and ELM","score":0.044199999421834946,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.00860000029206276,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.7706999778747559},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6697999835014343},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5098999738693237},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4948999881744385},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.448199987411499},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4075999855995178}],"concepts":[{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.7706999778747559},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6697999835014343},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5098999738693237},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4948999881744385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45100000500679016},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.448199987411499},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.40470001101493835},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.36649999022483826},{"id":"https://openalex.org/C2776895703","wikidata":"https://www.wikidata.org/wiki/Q6736207","display_name":"Main bearing","level":3,"score":0.362199991941452},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.32739999890327454},{"id":"https://openalex.org/C167391956","wikidata":"https://www.wikidata.org/wiki/Q1401211","display_name":"Fault model","level":3,"score":0.31439998745918274},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.31360000371932983},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2831000089645386},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27810001373291016}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/indin64977.2025.11279497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin64977.2025.11279497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 23rd International Conference on Industrial Informatics (INDIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320325433","display_name":"China National Tobacco Corporation","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2078994304","https://openalex.org/W2265788075","https://openalex.org/W2290883490","https://openalex.org/W2581853886","https://openalex.org/W2618530766","https://openalex.org/W2898760173","https://openalex.org/W2966008650","https://openalex.org/W3214367198","https://openalex.org/W4213237138","https://openalex.org/W4285195618","https://openalex.org/W4292852481","https://openalex.org/W4311058629","https://openalex.org/W4315866203","https://openalex.org/W4381112601","https://openalex.org/W4386759720","https://openalex.org/W4388918305","https://openalex.org/W4390300285","https://openalex.org/W4390955332","https://openalex.org/W4391164402"],"related_works":[],"abstract_inverted_index":{"As":[0],"a":[1,64],"key":[2],"component":[3],"of":[4,33,43,53],"industrial":[5],"equipment,":[6],"bearings":[7],"are":[8],"prone":[9],"to":[10],"failure":[11],"under":[12],"complex":[13],"operating":[14],"conditions.":[15],"Bearing":[16],"fault":[17,45,75,101],"diagnosis":[18,102],"can":[19],"detect":[20],"potential":[21],"dangers":[22],"at":[23],"an":[24],"early":[25],"stage,":[26],"thus":[27],"ensuring":[28],"the":[29,40,44,51,54,83,93],"stability":[30],"and":[31,48,103],"efficiency":[32],"production.":[34],"Existing":[35],"research":[36],"mainly":[37],"focuses":[38],"on":[39],"structural":[41],"improvement":[42],"classification":[46],"model":[47,72,78],"often":[49],"neglects":[50],"optimization":[52,86],"algorithm":[55,87],"parameters.":[56],"To":[57],"address":[58],"this":[59,61],"deficiency,":[60],"paper":[62],"proposed":[63,94],"hybrid":[65],"convolutional":[66],"neural":[67],"network-long":[68],"short-term":[69],"memory":[70],"(CNN-LSTM)":[71],"for":[73],"bearing":[74,100],"diagnosis.":[76],"The":[77],"parameters":[79],"were":[80],"optimized":[81],"using":[82],"improved":[84],"whale":[85],"(IWOA).":[88],"Experimental":[89],"results":[90],"show":[91],"that":[92],"method":[95],"has":[96,104],"superior":[97],"performance":[98],"in":[99],"broad":[105],"application":[106],"prospects.":[107]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-08T00:00:00"}
