{"id":"https://openalex.org/W4387976286","doi":"https://doi.org/10.3390/s23218769","title":"Detecting Helical Gearbox Defects from Raw Vibration Signal Using Convolutional Neural Networks","display_name":"Detecting Helical Gearbox Defects from Raw Vibration Signal Using Convolutional Neural Networks","publication_year":2023,"publication_date":"2023-10-27","ids":{"openalex":"https://openalex.org/W4387976286","doi":"https://doi.org/10.3390/s23218769","pmid":"https://pubmed.ncbi.nlm.nih.gov/37960469"},"language":"en","primary_location":{"id":"doi:10.3390/s23218769","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23218769","pdf_url":"https://www.mdpi.com/1424-8220/23/21/8769/pdf?version=1698400729","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/1424-8220/23/21/8769/pdf?version=1698400729","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010069108","display_name":"Iulian Lupea","orcid":"https://orcid.org/0000-0003-4024-0159"},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Iulian Lupea","raw_affiliation_strings":["Faculty of Industrial Engineering, Robotics and Production Management, Technical University of Cluj-Napoca, 400641 Cluj-Napoca, Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Industrial Engineering, Robotics and Production Management, Technical University of Cluj-Napoca, 400641 Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I158333966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074256643","display_name":"Mihaiela Lupea","orcid":"https://orcid.org/0000-0002-2117-2018"},"institutions":[{"id":"https://openalex.org/I3125347698","display_name":"Babe\u0219-Bolyai University","ror":"https://ror.org/02rmd1t30","country_code":"RO","type":"education","lineage":["https://openalex.org/I3125347698"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Mihaiela Lupea","raw_affiliation_strings":["Faculty of Mathematics and Computer Science, Babes-Bolyai University, 400084 Cluj-Napoca, Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Computer Science, Babes-Bolyai University, 400084 Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I3125347698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5010069108"],"corresponding_institution_ids":["https://openalex.org/I158333966"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":2.4093,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.88959767,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"23","issue":"21","first_page":"8769","last_page":"8769"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9970999956130981,"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":0.9847999811172485,"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/reducer","display_name":"Reducer","score":0.938866376876831},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.8000537157058716},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7162280678749084},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.6366132497787476},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5839227437973022},{"id":"https://openalex.org/keywords/actuator","display_name":"Actuator","score":0.5106988549232483},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4730255603790283},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.404821515083313},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38435596227645874},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36895132064819336},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.33584481477737427},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10365289449691772},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.08910036087036133}],"concepts":[{"id":"https://openalex.org/C2776985865","wikidata":"https://www.wikidata.org/wiki/Q26820931","display_name":"Reducer","level":2,"score":0.938866376876831},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.8000537157058716},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7162280678749084},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.6366132497787476},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5839227437973022},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.5106988549232483},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4730255603790283},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.404821515083313},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38435596227645874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36895132064819336},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.33584481477737427},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10365289449691772},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.08910036087036133},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s23218769","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23218769","pdf_url":"https://www.mdpi.com/1424-8220/23/21/8769/pdf?version=1698400729","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:37960469","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37960469","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:10647615","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10647615","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10647615/pdf/sensors-23-08769.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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:61ab95672957426fbaa8c787c0f3e541","is_oa":true,"landing_page_url":"https://doaj.org/article/61ab95672957426fbaa8c787c0f3e541","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":"Sensors, Vol 23, Iss 21, p 8769 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s23218769","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23218769","pdf_url":"https://www.mdpi.com/1424-8220/23/21/8769/pdf?version=1698400729","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5899999737739563},{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387976286.pdf"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1794079803","https://openalex.org/W2011296483","https://openalex.org/W2019055402","https://openalex.org/W2035094917","https://openalex.org/W2060487089","https://openalex.org/W2077896524","https://openalex.org/W2106578604","https://openalex.org/W2135246454","https://openalex.org/W2273449731","https://openalex.org/W2396076036","https://openalex.org/W2608571722","https://openalex.org/W2616321591","https://openalex.org/W2810292802","https://openalex.org/W2908973498","https://openalex.org/W2915514405","https://openalex.org/W2994928929","https://openalex.org/W2999930425","https://openalex.org/W3025512893","https://openalex.org/W3100777112","https://openalex.org/W3161130775","https://openalex.org/W3161439748","https://openalex.org/W4213046837","https://openalex.org/W4225839279","https://openalex.org/W4290517836","https://openalex.org/W4313327697"],"related_works":["https://openalex.org/W2394411596","https://openalex.org/W2599888081","https://openalex.org/W2349055795","https://openalex.org/W2943236215","https://openalex.org/W2737431648","https://openalex.org/W4226030716","https://openalex.org/W2725465928","https://openalex.org/W2358616404","https://openalex.org/W2352263435","https://openalex.org/W4308659732"],"abstract_inverted_index":{"A":[0,65],"study":[1],"on":[2,23,38,70,126,130],"the":[3,12,55,62,79,93,102,106,111,127,131,135,145,151,160,163,165,180,188,191],"gearbox":[4,192],"(speed":[5],"reducer)":[6],"defect":[7],"detection":[8,116],"models":[9,168],"built":[10,178],"from":[11,78,144,182],"raw":[13],"vibration":[14,80,141],"signal":[15,83],"measured":[16,129],"by":[17],"a":[18,119],"triaxial":[19],"accelerometer":[20,152,185],"and":[21,43,57,98,147,171],"based":[22,69],"convolutional":[24],"neural":[25],"networks":[26],"(CNNs)":[27],"is":[28,74],"presented.":[29],"Gear":[30],"faults":[31],"such":[32],"as":[33],"localized":[34,36],"pitting,":[35],"wear":[37],"helical":[39],"pinion":[40],"tooth":[41],"flanks,":[42],"lubricant":[44],"low":[45],"level":[46,109],"are":[47,86],"under":[48],"observation":[49],"for":[50],"three":[51,58,99,184],"rotating":[52],"velocities":[53],"of":[54,92,101,105,122,150,162,190,196],"actuator":[56],"load":[59,108],"levels":[60],"at":[61],"reducer":[63,136],"output.":[64],"deep":[66],"learning":[67],"approach,":[68],"1D-CNN":[71],"or":[72,110],"2D-CNN,":[73],"employed":[75],"to":[76,89,154],"extract":[77],"image":[81],"significant":[82],"features":[84],"that":[85],"used":[87],"further":[88],"identify":[90],"one":[91],"four":[94],"states":[95,161],"(one":[96],"normal":[97],"defects)":[100],"system,":[103],"regardless":[104],"selected":[107],"speed.":[112],"The":[113,140,175],"best-performing":[114],"1D-CNN-based":[115,167],"model,":[117,177],"with":[118,193],"testing":[120,173],"accuracy":[121,195],"98.91%,":[123],"was":[124],"trained":[125],"signals":[128],"Y":[132],"axis":[133],"along":[134],"input":[137],"shaft":[138],"direction.":[139],"data":[142,181],"acquired":[143],"X":[146],"Z":[148],"axes":[149],"proved":[153],"be":[155],"less":[156],"relevant":[157],"in":[158],"discriminating":[159],"gearbox,":[164],"corresponding":[166],"achieving":[169],"97.15%":[170],"97%":[172],"accuracy.":[174],"2D-CNN-based":[176],"using":[179],"all":[183],"axes,":[186],"detects":[187],"state":[189],"an":[194],"99.63%.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":8}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
