{"id":"https://openalex.org/W4399207448","doi":"https://doi.org/10.1109/access.2024.3407766","title":"Optimizing Detection: Compact MobileNet Models for Precise Hall Sensor Fault Identification in BLDC Motor Drives","display_name":"Optimizing Detection: Compact MobileNet Models for Precise Hall Sensor Fault Identification in BLDC Motor Drives","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399207448","doi":"https://doi.org/10.1109/access.2024.3407766"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3407766","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3407766","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3407766","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068547596","display_name":"Seul Ki Hong","orcid":"https://orcid.org/0009-0000-8754-0306"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Seul Ki Hong","raw_affiliation_strings":["Department of Semiconductor Engineering, Seoul National University of Science and Technology, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0009-0000-8754-0306","affiliations":[{"raw_affiliation_string":"Department of Semiconductor Engineering, Seoul National University of Science and Technology, Seoul, South Korea","institution_ids":["https://openalex.org/I118373667"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027140824","display_name":"YongKeun Lee","orcid":"https://orcid.org/0000-0003-0789-8354"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yongkeun Lee","raw_affiliation_strings":["Department of Semiconductor Engineering, Seoul National University of Science and Technology, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-0789-8354","affiliations":[{"raw_affiliation_string":"Department of Semiconductor Engineering, Seoul National University of Science and Technology, Seoul, South Korea","institution_ids":["https://openalex.org/I118373667"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5068547596"],"corresponding_institution_ids":["https://openalex.org/I118373667"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.8554,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.85019398,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"77475","last_page":"77485"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9905999898910522,"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":0.9905999898910522,"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":0.9779000282287598,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9702000021934509,"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/computer-science","display_name":"Computer science","score":0.7427744269371033},{"id":"https://openalex.org/keywords/hall-effect-sensor","display_name":"Hall effect sensor","score":0.6373178362846375},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.623049259185791},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5654470920562744},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4733861982822418},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45460033416748047},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3342869281768799},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30228689312934875},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13906767964363098},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.11552694439888},{"id":"https://openalex.org/keywords/actuator","display_name":"Actuator","score":0.09287431836128235},{"id":"https://openalex.org/keywords/magnet","display_name":"Magnet","score":0.06752997636795044}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7427744269371033},{"id":"https://openalex.org/C107637996","wikidata":"https://www.wikidata.org/wiki/Q1431247","display_name":"Hall effect sensor","level":3,"score":0.6373178362846375},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.623049259185791},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5654470920562744},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4733861982822418},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45460033416748047},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3342869281768799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30228689312934875},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13906767964363098},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.11552694439888},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.09287431836128235},{"id":"https://openalex.org/C16389437","wikidata":"https://www.wikidata.org/wiki/Q11421","display_name":"Magnet","level":2,"score":0.06752997636795044},{"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3407766","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3407766","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:34f1e27b6e394d32bde7f63b6e8d0f7d","is_oa":true,"landing_page_url":"https://doaj.org/article/34f1e27b6e394d32bde7f63b6e8d0f7d","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":"IEEE Access, Vol 12, Pp 77475-77485 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3407766","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3407766","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321294","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1978232906","https://openalex.org/W2025533812","https://openalex.org/W2041964770","https://openalex.org/W2056538626","https://openalex.org/W2166030461","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2284974496","https://openalex.org/W2304858949","https://openalex.org/W2531409750","https://openalex.org/W2603287839","https://openalex.org/W2776855315","https://openalex.org/W2790180303","https://openalex.org/W2805234550","https://openalex.org/W2810057162","https://openalex.org/W2889644327","https://openalex.org/W2938828471","https://openalex.org/W2955425717","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2968369946","https://openalex.org/W2979205926","https://openalex.org/W2992226985","https://openalex.org/W3041133507","https://openalex.org/W3161442774","https://openalex.org/W3164334355","https://openalex.org/W3167451637","https://openalex.org/W3173724856","https://openalex.org/W3198793860","https://openalex.org/W4236362309","https://openalex.org/W4285278316","https://openalex.org/W4289922212","https://openalex.org/W4297775537","https://openalex.org/W4313148215","https://openalex.org/W4362683514","https://openalex.org/W4367317667","https://openalex.org/W4382981550","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6686164453","https://openalex.org/W6687483927","https://openalex.org/W6725739302","https://openalex.org/W6728184133","https://openalex.org/W6737664043","https://openalex.org/W6747043858","https://openalex.org/W6762718338"],"related_works":["https://openalex.org/W2370979685","https://openalex.org/W3162919010","https://openalex.org/W2586454696","https://openalex.org/W2187844424","https://openalex.org/W2365721267","https://openalex.org/W2787993192","https://openalex.org/W2189291528","https://openalex.org/W3141207015","https://openalex.org/W2408343962","https://openalex.org/W2078455782"],"abstract_inverted_index":{"This":[0,143],"paper":[1],"presents":[2],"a":[3,147],"comprehensive":[4],"study":[5],"on":[6],"fault":[7,48,155],"identification":[8],"in":[9,117,157],"Hall":[10,60,119,153],"sensors":[11],"within":[12],"Brushless":[13],"Direct":[14],"Current":[15],"(BLDC)":[16],"motor":[17,29,159],"drives":[18],"using":[19],"neural":[20,50,97],"networks.":[21],"Detecting":[22],"these":[23],"faults":[24],"is":[25,40],"critical":[26],"for":[27,53,152],"optimizing":[28],"performance,":[30],"enhancing":[31],"energy":[32],"efficiency,":[33],"and":[34,46,56,69,80,92,106,134,149],"ensuring":[35],"overall":[36],"reliability.":[37],"Our":[38,110],"objective":[39],"to":[41,59,71,76,100],"propose":[42],"an":[43,135],"accurate,":[44,104],"compact,":[45],"efficient":[47,150],"detection":[49,156],"network":[51,98],"model":[52],"real-time":[54],"monitoring":[55],"swift":[57],"responses":[58],"sensor":[61,120,154],"faults.":[62],"Conventional":[63],"methods":[64],"are":[65],"often":[66],"computationally":[67],"demanding":[68],"fail":[70],"detect":[72],"subtle":[73],"faults,":[74,121],"leading":[75],"significant":[77],"performance":[78],"decline":[79],"potential":[81],"catastrophic":[82],"failures.":[83],"To":[84],"address":[85],"this,":[86],"we":[87],"leverage":[88],"MobileNet-based":[89],"compact":[90],"models":[91,99,115],"compare":[93],"them":[94],"with":[95,126],"state-of-the-art":[96],"identify":[101],"the":[102],"most":[103],"lightweight,":[105],"fast":[107],"inference":[108,137],"option.":[109],"findings":[111],"demonstrate":[112],"that":[113],"MobileNet":[114,145],"excel":[116],"detecting":[118],"achieving":[122],"over":[123],"90%":[124],"accuracy":[125],"significantly":[127],"fewer":[128],"parameters":[129],"(less":[130],"than":[131],"five":[132],"million)":[133],"impressive":[136],"time":[138],"of":[139],"under":[140],"25":[141],"milliseconds.":[142],"highlights":[144],"as":[146],"robust":[148],"choice":[151],"BLDC":[158],"drives.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
