{"id":"https://openalex.org/W4229000217","doi":"https://doi.org/10.3390/s22093516","title":"Modeling and Fault Detection of Brushless Direct Current Motor by Deep Learning Sensor Data Fusion","display_name":"Modeling and Fault Detection of Brushless Direct Current Motor by Deep Learning Sensor Data Fusion","publication_year":2022,"publication_date":"2022-05-05","ids":{"openalex":"https://openalex.org/W4229000217","doi":"https://doi.org/10.3390/s22093516","pmid":"https://pubmed.ncbi.nlm.nih.gov/35591209"},"language":"en","primary_location":{"id":"doi:10.3390/s22093516","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22093516","pdf_url":"https://www.mdpi.com/1424-8220/22/9/3516/pdf?version=1651752022","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/1424-8220/22/9/3516/pdf?version=1651752022","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065301991","display_name":"Priscile Fogou Suawa","orcid":"https://orcid.org/0000-0002-0404-2043"},"institutions":[{"id":"https://openalex.org/I51783024","display_name":"Brandenburg University of Technology Cottbus-Senftenberg","ror":"https://ror.org/02wxx3e24","country_code":"DE","type":"education","lineage":["https://openalex.org/I51783024"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Priscile Suawa","raw_affiliation_strings":["Department of Computer Engineering, Brandenburg University of Technology Cottbus-Senftenberg, 03046 Cottbus, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Brandenburg University of Technology Cottbus-Senftenberg, 03046 Cottbus, Germany","institution_ids":["https://openalex.org/I51783024"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073776536","display_name":"Tenia Meisel","orcid":null},"institutions":[{"id":"https://openalex.org/I4210110247","display_name":"Fraunhofer Institute for Photonic Microsystems","ror":"https://ror.org/020n3fw10","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210110247","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tenia Meisel","raw_affiliation_strings":["Fraunhofer Institute for Photonic Microsystems, 01109 Dresden, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Photonic Microsystems, 01109 Dresden, Germany","institution_ids":["https://openalex.org/I4210110247"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050451934","display_name":"Marcel Jongmanns","orcid":"https://orcid.org/0000-0001-8595-7749"},"institutions":[{"id":"https://openalex.org/I4210110247","display_name":"Fraunhofer Institute for Photonic Microsystems","ror":"https://ror.org/020n3fw10","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210110247","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marcel Jongmanns","raw_affiliation_strings":["Fraunhofer Institute for Photonic Microsystems, 01109 Dresden, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Photonic Microsystems, 01109 Dresden, Germany","institution_ids":["https://openalex.org/I4210110247"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039658584","display_name":"Michael Huebner","orcid":"https://orcid.org/0000-0002-1790-3869"},"institutions":[{"id":"https://openalex.org/I51783024","display_name":"Brandenburg University of Technology Cottbus-Senftenberg","ror":"https://ror.org/02wxx3e24","country_code":"DE","type":"education","lineage":["https://openalex.org/I51783024"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Huebner","raw_affiliation_strings":["Department of Computer Engineering, Brandenburg University of Technology Cottbus-Senftenberg, 03046 Cottbus, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Brandenburg University of Technology Cottbus-Senftenberg, 03046 Cottbus, Germany","institution_ids":["https://openalex.org/I51783024"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014794132","display_name":"Marc Reichenbach","orcid":"https://orcid.org/0000-0002-9687-6247"},"institutions":[{"id":"https://openalex.org/I51783024","display_name":"Brandenburg University of Technology Cottbus-Senftenberg","ror":"https://ror.org/02wxx3e24","country_code":"DE","type":"education","lineage":["https://openalex.org/I51783024"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marc Reichenbach","raw_affiliation_strings":["Department of Computer Engineering, Brandenburg University of Technology Cottbus-Senftenberg, 03046 Cottbus, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Brandenburg University of Technology Cottbus-Senftenberg, 03046 Cottbus, Germany","institution_ids":["https://openalex.org/I51783024"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5065301991"],"corresponding_institution_ids":["https://openalex.org/I51783024"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":4.6062,"has_fulltext":true,"cited_by_count":40,"citation_normalized_percentile":{"value":0.95280185,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"22","issue":"9","first_page":"3516","last_page":"3516"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9979000091552734,"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":0.9979000091552734,"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":0.9923999905586243,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9912999868392944,"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/computer-science","display_name":"Computer science","score":0.7467813491821289},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.604669988155365},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5999857783317566},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5879467725753784},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.581123411655426},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4633392095565796},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4507552981376648},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.4497872292995453},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.4434163570404053},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.4334411025047302},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4280809462070465},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4279245138168335},{"id":"https://openalex.org/keywords/microphone","display_name":"Microphone","score":0.42252233624458313},{"id":"https://openalex.org/keywords/actuator","display_name":"Actuator","score":0.1332779824733734}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7467813491821289},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.604669988155365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5999857783317566},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5879467725753784},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.581123411655426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4633392095565796},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4507552981376648},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.4497872292995453},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.4434163570404053},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.4334411025047302},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4280809462070465},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4279245138168335},{"id":"https://openalex.org/C2778263558","wikidata":"https://www.wikidata.org/wiki/Q46384","display_name":"Microphone","level":3,"score":0.42252233624458313},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.1332779824733734},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"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/C68115822","wikidata":"https://www.wikidata.org/wiki/Q1068172","display_name":"Sound pressure","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004560","descriptor_name":"Electricity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004560","descriptor_name":"Electricity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004560","descriptor_name":"Electricity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":6,"locations":[{"id":"doi:10.3390/s22093516","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22093516","pdf_url":"https://www.mdpi.com/1424-8220/22/9/3516/pdf?version=1651752022","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:35591209","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35591209","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:doaj.org/article:3859d04899774de19fc1bf8c4f331299","is_oa":true,"landing_page_url":"https://doaj.org/article/3859d04899774de19fc1bf8c4f331299","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 22, Iss 9, p 3516 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/9/3516/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22093516","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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; Volume 22; Issue 9; Pages: 3516","raw_type":"Text"},{"id":"pmh:oai:null:publica/429065","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/429065","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"journal article"},{"id":"pmh:oai:pubmedcentral.nih.gov:9099980","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9099980","pdf_url":null,"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"}],"best_oa_location":{"id":"doi:10.3390/s22093516","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22093516","pdf_url":"https://www.mdpi.com/1424-8220/22/9/3516/pdf?version=1651752022","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":[{"id":"https://metadata.un.org/sdg/16","score":0.5899999737739563,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4229000217.pdf","grobid_xml":"https://content.openalex.org/works/W4229000217.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1606187070","https://openalex.org/W2017774918","https://openalex.org/W2118542129","https://openalex.org/W2130786683","https://openalex.org/W2151177243","https://openalex.org/W2540779824","https://openalex.org/W2567958130","https://openalex.org/W2589171657","https://openalex.org/W2603304445","https://openalex.org/W2760345791","https://openalex.org/W2763079654","https://openalex.org/W2765767940","https://openalex.org/W2791939925","https://openalex.org/W2792461833","https://openalex.org/W2801346558","https://openalex.org/W2885406270","https://openalex.org/W2888865870","https://openalex.org/W2914447147","https://openalex.org/W2940953547","https://openalex.org/W3005770546","https://openalex.org/W3033236487","https://openalex.org/W3033399219","https://openalex.org/W3035669655","https://openalex.org/W3041632065","https://openalex.org/W3045897451","https://openalex.org/W3090238656","https://openalex.org/W3095711016","https://openalex.org/W3119634645","https://openalex.org/W3181101419","https://openalex.org/W4200131991","https://openalex.org/W4205562341","https://openalex.org/W4206493885","https://openalex.org/W4214913031","https://openalex.org/W6753653871"],"related_works":["https://openalex.org/W2765080098","https://openalex.org/W2385749422","https://openalex.org/W2355290145","https://openalex.org/W2353465659","https://openalex.org/W2009888974","https://openalex.org/W2355539379","https://openalex.org/W2056341223","https://openalex.org/W3023105672","https://openalex.org/W4231410700","https://openalex.org/W2042723094"],"abstract_inverted_index":{"Only":[0],"with":[1,95,164,234,298],"new":[2],"sensor":[3,65,98,134,162],"concepts":[4],"in":[5,139,210,264],"a":[6,38,73,117,124,140,146,199,253,271],"network,":[7],"which":[8,48],"go":[9],"far":[10],"beyond":[11],"what":[12],"the":[13,42,58,89,184,187,202,228,231,244,265,268,278,281],"current":[14,19,127],"state-of-the-art":[15],"can":[16,18,49],"offer,":[17],"and":[20,26,52,68,78,119,193,237,241,247,283,304,315,323,330],"future":[21],"requirements":[22],"for":[23,149,175,220,243,327],"flexibility,":[24],"safety,":[25],"security":[27],"be":[28],"met.":[29],"The":[30,130,206],"combination":[31,92,200],"of":[32,41,60,93,201,230,267,270,280],"data":[33,66,112,131,235,300,331],"from":[34,80,114,132,183,301],"many":[35],"sensors":[36,94,303],"allows":[37],"richer":[39],"representation":[40],"observed":[43],"phenomenon,":[44],"e.g.,":[45],"system":[46],"degradation,":[47],"facilitate":[50],"analysis":[51,266],"decision-making":[53],"processes.":[54],"This":[55],"work":[56,157,297],"addresses":[57],"topic":[59],"predictive":[61,103],"maintenance":[62],"by":[63,286],"exploiting":[64],"fusion":[67,99,163,236,285],"artificial":[69],"intelligence-based":[70],"analysis.":[71,150],"With":[72],"dataset":[74],"such":[75,168],"as":[76,169],"vibration":[77],"sound":[79,213],"sensors,":[81,116],"we":[82,109],"focus":[83],"on":[84,123,317],"studying":[85],"paradigms":[86],"that":[87,209,292],"orchestrate":[88],"most":[90],"optimal":[91],"deep":[96,165,170,309],"learning":[97,166,310],"algorithms":[100],"to":[101,144,159,178,257,296,321,325],"enable":[102],"maintenance.":[104],"In":[105],"our":[106,211,258],"experimental":[107],"setup,":[108,212],"used":[110,218],"raw":[111,299],"obtained":[113],"two":[115,203],"microphone,":[118],"an":[120],"accelerometer":[121],"installed":[122],"brushless":[125],"direct":[126],"(BLDC)":[128],"motor.":[129],"each":[133],"were":[135],"processed":[136],"individually":[137,219],"and,":[138],"second":[141],"step,":[142,227],"merged":[143],"create":[145],"solid":[147],"base":[148],"To":[151],"diagnose":[152],"BLDC":[153,272],"motor":[154,273],"faults,":[155],"this":[156],"proposes":[158],"use":[160,326],"data-level":[161],"methods":[167,311,324],"convolutional":[171,194],"neural":[172],"networks":[173],"(DCNNs)":[174],"their":[176,284],"ability":[177],"automatically":[179],"extract":[180,322],"relevant":[181],"information":[182],"input":[185],"data,":[186],"long":[188,195],"short-term":[189,196],"memory":[190,197],"method":[191],"(LSTM),":[192],"(CNN-LSTM),":[198],"previous":[204],"methods.":[205,288],"results":[207,290,307],"show":[208,291],"signals":[214],"outperform":[215],"vibrations":[216],"when":[217],"training.":[221],"However,":[222],"without":[223,274,312],"any":[224],"feature":[225,328],"selection/extraction":[226],"accuracy":[229],"models":[232],"improves":[233],"reaches":[238],"98.8%,":[239],"93.5%,":[240],"73.6%":[242],"DCNN,":[245],"CNN-LSTM,":[246],"LSTM":[248],"methods,":[249],"respectively,":[250],"98.8%":[251],"being":[252],"performance":[254],"that,":[255],"according":[256],"reading,":[259],"has":[260],"never":[261],"been":[262],"reached":[263],"faults":[269],"first":[275],"going":[276],"through":[277],"extraction":[279,329],"characteristics":[282],"traditional":[287],"These":[289],"it":[293],"is":[294],"possible":[295],"multiple":[302],"achieve":[305],"good":[306],"using":[308],"spending":[313],"time":[314],"resources":[316],"selecting":[318],"appropriate":[319],"features":[320],"fusion.":[332]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
