{"id":"https://openalex.org/W7128534050","doi":"https://doi.org/10.3390/a19020144","title":"A Multimodal Three-Channel Bearing Fault Diagnosis Method Based on CNN Fusion Attention Mechanism Under Strong Noise Conditions","display_name":"A Multimodal Three-Channel Bearing Fault Diagnosis Method Based on CNN Fusion Attention Mechanism Under Strong Noise Conditions","publication_year":2026,"publication_date":"2026-02-10","ids":{"openalex":"https://openalex.org/W7128534050","doi":"https://doi.org/10.3390/a19020144"},"language":"en","primary_location":{"id":"doi:10.3390/a19020144","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a19020144","pdf_url":null,"source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"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":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/a19020144","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123139693","display_name":"Yingyong Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I49232843","display_name":"Changchun University","ror":"https://ror.org/02an57k10","country_code":"CN","type":"education","lineage":["https://openalex.org/I49232843"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingyong Zou","raw_affiliation_strings":["College of Mechanical and Vehicular Engineering, Changchun University, Changchun 130022, China"],"raw_orcid":"https://orcid.org/0000-0003-1569-0764","affiliations":[{"raw_affiliation_string":"College of Mechanical and Vehicular Engineering, Changchun University, Changchun 130022, China","institution_ids":["https://openalex.org/I49232843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102185856","display_name":"Chunfang Li","orcid":"https://orcid.org/0009-0003-8986-8040"},"institutions":[{"id":"https://openalex.org/I49232843","display_name":"Changchun University","ror":"https://ror.org/02an57k10","country_code":"CN","type":"education","lineage":["https://openalex.org/I49232843"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunfang Li","raw_affiliation_strings":["College of Mechanical and Vehicular Engineering, Changchun University, Changchun 130022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechanical and Vehicular Engineering, Changchun University, Changchun 130022, China","institution_ids":["https://openalex.org/I49232843"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yu Zhang","orcid":"https://orcid.org/0009-0006-0516-9819"},"institutions":[{"id":"https://openalex.org/I49232843","display_name":"Changchun University","ror":"https://ror.org/02an57k10","country_code":"CN","type":"education","lineage":["https://openalex.org/I49232843"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zhang","raw_affiliation_strings":["College of Mechanical and Vehicular Engineering, Changchun University, Changchun 130022, China"],"raw_orcid":"https://orcid.org/0009-0006-0516-9819","affiliations":[{"raw_affiliation_string":"College of Mechanical and Vehicular Engineering, Changchun University, Changchun 130022, China","institution_ids":["https://openalex.org/I49232843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123147849","display_name":"Zhiqiang Si","orcid":null},"institutions":[{"id":"https://openalex.org/I49232843","display_name":"Changchun University","ror":"https://ror.org/02an57k10","country_code":"CN","type":"education","lineage":["https://openalex.org/I49232843"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Si","raw_affiliation_strings":["College of Mechanical and Vehicular Engineering, Changchun University, Changchun 130022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechanical and Vehicular Engineering, Changchun University, Changchun 130022, China","institution_ids":["https://openalex.org/I49232843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125517843","display_name":"Long Li","orcid":null},"institutions":[{"id":"https://openalex.org/I49232843","display_name":"Changchun University","ror":"https://ror.org/02an57k10","country_code":"CN","type":"education","lineage":["https://openalex.org/I49232843"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Li","raw_affiliation_strings":["College of Mechanical and Vehicular Engineering, Changchun University, Changchun 130022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechanical and Vehicular Engineering, Changchun University, Changchun 130022, China","institution_ids":["https://openalex.org/I49232843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5123139693"],"corresponding_institution_ids":["https://openalex.org/I49232843"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1782},"fwci":5.2756,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92854726,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"19","issue":"2","first_page":"144","last_page":"144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9884999990463257,"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":0.9884999990463257,"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":0.0017999999690800905,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.0010999999940395355,"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/noise-reduction","display_name":"Noise reduction","score":0.6872000098228455},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6014000177383423},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5401999950408936},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5257999897003174},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.48829999566078186},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.48429998755455017},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4837000072002411},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.48089998960494995},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.47540000081062317}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7972999811172485},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6872000098228455},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6437000036239624},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6014000177383423},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5401999950408936},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5257999897003174},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.48829999566078186},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.48429998755455017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4837000072002411},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48089998960494995},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.47540000081062317},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41600000858306885},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.41449999809265137},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3528999984264374},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34929999709129333},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.33719998598098755},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.2513999938964844}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/a19020144","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a19020144","pdf_url":null,"source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"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":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:cbf1ccf9e8a84f15906de9a6d1b60a58","is_oa":false,"landing_page_url":"https://doaj.org/article/cbf1ccf9e8a84f15906de9a6d1b60a58","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 19, Iss 2, p 144 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/a19020144","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a19020144","pdf_url":null,"source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"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":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4720400273799896}],"awards":[{"id":"https://openalex.org/G1245720335","display_name":null,"funder_award_id":"20230101208JC","funder_id":"https://openalex.org/F4320327282","funder_display_name":"Department of Science and Technology of Jilin Province"}],"funders":[{"id":"https://openalex.org/F4320327282","display_name":"Department of Science and Technology of Jilin Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2277064738","https://openalex.org/W2483704186","https://openalex.org/W2801396593","https://openalex.org/W2990122260","https://openalex.org/W3015173390","https://openalex.org/W3037060082","https://openalex.org/W3138516171","https://openalex.org/W3173686483","https://openalex.org/W3203494009","https://openalex.org/W4312194501","https://openalex.org/W4382403155","https://openalex.org/W4385346926","https://openalex.org/W4386435381","https://openalex.org/W4387056581","https://openalex.org/W4393125942","https://openalex.org/W4393185885","https://openalex.org/W4394930757","https://openalex.org/W4398764972","https://openalex.org/W4399990749","https://openalex.org/W4402742551","https://openalex.org/W4404343884","https://openalex.org/W4406250678","https://openalex.org/W4406633398","https://openalex.org/W4409814731","https://openalex.org/W4410124341","https://openalex.org/W4410203008","https://openalex.org/W7106105108"],"related_works":[],"abstract_inverted_index":{"Bearings,":[0],"as":[1],"core":[2],"components":[3],"of":[4,26,40,80,113,148,192],"mechanical":[5],"equipment,":[6],"play":[7],"a":[8,45,51,59,64,91,121,213,226],"critical":[9],"role":[10],"in":[11,29,83,250],"ensuring":[12],"equipment":[13],"safety":[14],"and":[15,37,117,145,156,198,238],"reliability.":[16],"Early":[17],"fault":[18,31,42,54,153,248],"detection":[19],"holds":[20],"significant":[21],"importance.":[22],"Addressing":[23],"the":[24,38,77,111,129,163,182,196,221],"challenges":[25],"insufficient":[27],"robustness":[28],"bearing":[30,81,247],"diagnosis":[32,55,79,126,154,249],"under":[33,173,206],"industrial":[34,251],"high-noise":[35,84],"conditions":[36],"difficulty":[39],"extracting":[41],"features":[43],"from":[44],"single":[46,227],"modality,":[47],"this":[48],"study":[49],"proposes":[50],"three-channel":[52,122],"multimodal":[53],"method":[56],"that":[57,162],"integrates":[58],"Convolutional":[60],"Auto-Encoder":[61],"(CAE)":[62],"with":[63,134,181,253],"dual":[65],"attention":[66,136],"mechanism":[67,137],"(M-CNNBiAM).":[68],"This":[69,140],"approach":[70,141],"provides":[71],"an":[72,135,188],"effective":[73],"technical":[74],"solution":[75],"for":[76,105,244],"precise":[78],"faults":[82],"environments.":[85],"To":[86,109],"suppress":[87],"substantial":[88],"noise":[89,169,177,209,255],"interference,":[90],"CAE":[92,165,222],"denoising":[93,223],"module":[94,166],"was":[95,138],"designed":[96,164],"to":[97],"filter":[98],"out":[99],"intense":[100],"noise,":[101],"providing":[102],"high-quality":[103],"input":[104],"subsequent":[106],"diagnostic":[107,184,190,203,215,239],"networks.":[108],"address":[110],"limitations":[112],"single-modal":[114],"feature":[115],"extraction":[116],"restricted":[118],"generalization":[119,157],"capabilities,":[120],"time\u2013frequency":[123],"signal":[124],"joint":[125],"model":[127],"combining":[128],"Continuous":[130],"Wavelet":[131],"Transform":[132],"(CWT)":[133],"proposed.":[139],"enables":[142],"deep":[143],"mining":[144],"efficient":[146],"fusion":[147],"multi-domain":[149],"features,":[150],"thereby":[151],"enhancing":[152],"accuracy":[155,191,216],"capabilities.":[158],"Experimental":[159],"results":[160],"demonstrate":[161],"maintains":[167],"excellent":[168],"reduction":[170],"performance":[171],"even":[172,217],"\u221210":[174],"dB":[175,208],"strong":[176],"conditions.":[178],"When":[179],"combined":[180],"proposed":[183],"model,":[185],"it":[186,211,234,242],"achieves":[187,212],"average":[189],"98%":[193],"across":[194],"both":[195],"CWRU":[197],"self-test":[199],"datasets,":[200],"demonstrating":[201],"outstanding":[202],"precision.":[204],"Furthermore,":[205],"\u22124":[207],"conditions,":[210],"94%":[214],"without":[218],"relying":[219],"on":[220],"module.":[224],"With":[225],"training":[228,236],"cycle":[229],"taking":[230],"only":[231],"6.8":[232],"s,":[233],"balances":[235],"efficiency":[237],"performance,":[240],"making":[241],"well-suited":[243],"real-time,":[245],"reliable":[246],"environments":[252],"high":[254],"levels.":[256]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-02-11T00:00:00"}
