{"id":"https://openalex.org/W4417052607","doi":"https://doi.org/10.1109/lars69345.2025.11272963","title":"Lightweight CNN-Based Acoustic Monitoring for Real-Time UAV Propeller Anomaly Detection","display_name":"Lightweight CNN-Based Acoustic Monitoring for Real-Time UAV Propeller Anomaly Detection","publication_year":2025,"publication_date":"2025-10-29","ids":{"openalex":"https://openalex.org/W4417052607","doi":"https://doi.org/10.1109/lars69345.2025.11272963"},"language":null,"primary_location":{"id":"doi:10.1109/lars69345.2025.11272963","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lars69345.2025.11272963","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Latin American Robotics Symposium (LARS)","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/A5120640156","display_name":"Javier Fuentes-Sanchez","orcid":null},"institutions":[{"id":"https://openalex.org/I39824353","display_name":"National Institute of Astrophysics, Optics and Electronics","ror":"https://ror.org/00bpmmc63","country_code":"MX","type":"facility","lineage":["https://openalex.org/I39824353"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Javier Fuentes-Sanchez","raw_affiliation_strings":["Instituto Nacional de Astrof&#x00ED;sica, &#x00D3;ptica y Electr&#x00F3;nica, Luis Enrique Erro No. 1, Santa Mar&#x00ED;a Tonantzintla, San Andr&#x00E9;s Cholula,Coordinaci&#x00F3;n de Electr&#x00F3;nica,Puebla,Mexico,72840"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Nacional de Astrof&#x00ED;sica, &#x00D3;ptica y Electr&#x00F3;nica, Luis Enrique Erro No. 1, Santa Mar&#x00ED;a Tonantzintla, San Andr&#x00E9;s Cholula,Coordinaci&#x00F3;n de Electr&#x00F3;nica,Puebla,Mexico,72840","institution_ids":["https://openalex.org/I39824353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043033361","display_name":"Jos\u00e9 Hugo Barr\u00f3n-Zambrano","orcid":"https://orcid.org/0000-0002-0965-6714"},"institutions":[{"id":"https://openalex.org/I39824353","display_name":"National Institute of Astrophysics, Optics and Electronics","ror":"https://ror.org/00bpmmc63","country_code":"MX","type":"facility","lineage":["https://openalex.org/I39824353"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Jose Barron-Zambrano","raw_affiliation_strings":["Instituto Nacional de Astrof&#x00ED;sica, &#x00D3;ptica y Electr&#x00F3;nica, Luis Enrique Erro No. 1, Santa Mar&#x00ED;a Tonantzintla, San Andr&#x00E9;s Cholula,Coordinaci&#x00F3;n de Electr&#x00F3;nica,Puebla,Mexico,72840"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Nacional de Astrof&#x00ED;sica, &#x00D3;ptica y Electr&#x00F3;nica, Luis Enrique Erro No. 1, Santa Mar&#x00ED;a Tonantzintla, San Andr&#x00E9;s Cholula,Coordinaci&#x00F3;n de Electr&#x00F3;nica,Puebla,Mexico,72840","institution_ids":["https://openalex.org/I39824353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010423760","display_name":"Jose Rangel\u2010Magdaleno","orcid":"https://orcid.org/0000-0003-2785-5060"},"institutions":[{"id":"https://openalex.org/I39824353","display_name":"National Institute of Astrophysics, Optics and Electronics","ror":"https://ror.org/00bpmmc63","country_code":"MX","type":"facility","lineage":["https://openalex.org/I39824353"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Jose Rangel-Magdaleno","raw_affiliation_strings":["Instituto Nacional de Astrof&#x00ED;sica, &#x00D3;ptica y Electr&#x00F3;nica, Luis Enrique Erro No. 1, Santa Mar&#x00ED;a Tonantzintla, San Andr&#x00E9;s Cholula,Coordinaci&#x00F3;n de Electr&#x00F3;nica,Puebla,Mexico,72840"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Nacional de Astrof&#x00ED;sica, &#x00D3;ptica y Electr&#x00F3;nica, Luis Enrique Erro No. 1, Santa Mar&#x00ED;a Tonantzintla, San Andr&#x00E9;s Cholula,Coordinaci&#x00F3;n de Electr&#x00F3;nica,Puebla,Mexico,72840","institution_ids":["https://openalex.org/I39824353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063313091","display_name":"\u00c1lvaro Hern\u00e1ndez","orcid":"https://orcid.org/0000-0001-9308-8133"},"institutions":[{"id":"https://openalex.org/I189268942","display_name":"Universidad de Alcal\u00e1","ror":"https://ror.org/04pmn0e78","country_code":"ES","type":"education","lineage":["https://openalex.org/I189268942"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Alvaro Hernandez","raw_affiliation_strings":["Universidad de Alcal&#x00E1;,Electronics Department,Alcal&#x00E1; de Henares,Espa&#x00F1;a"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad de Alcal&#x00E1;,Electronics Department,Alcal&#x00E1; de Henares,Espa&#x00F1;a","institution_ids":["https://openalex.org/I189268942"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44700323,"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/T11133","display_name":"UAV Applications and Optimization","score":0.1354999989271164,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11133","display_name":"UAV Applications and Optimization","score":0.1354999989271164,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.13259999454021454,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.10819999873638153,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5947999954223633},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5699999928474426},{"id":"https://openalex.org/keywords/propeller","display_name":"Propeller","score":0.44029998779296875},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.4250999987125397},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3919000029563904},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.3716000020503998},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3513999879360199}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6466000080108643},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5947999954223633},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5699999928474426},{"id":"https://openalex.org/C80055088","wikidata":"https://www.wikidata.org/wiki/Q205451","display_name":"Propeller","level":2,"score":0.44029998779296875},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4334999918937683},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.4250999987125397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41920000314712524},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3919000029563904},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.3716000020503998},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3513999879360199},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34060001373291016},{"id":"https://openalex.org/C2776247918","wikidata":"https://www.wikidata.org/wiki/Q1423713","display_name":"Structural health monitoring","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lars69345.2025.11272963","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lars69345.2025.11272963","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Latin American Robotics Symposium (LARS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2298275666","https://openalex.org/W2921056357","https://openalex.org/W2945498092","https://openalex.org/W3045731307","https://openalex.org/W3186446693","https://openalex.org/W3213151440","https://openalex.org/W4223960724","https://openalex.org/W4281695827","https://openalex.org/W4285122155","https://openalex.org/W4285326546","https://openalex.org/W4285336819","https://openalex.org/W4307958490","https://openalex.org/W4308659632","https://openalex.org/W4382050594","https://openalex.org/W4386737207","https://openalex.org/W4409985748","https://openalex.org/W4412742999"],"related_works":[],"abstract_inverted_index":{"Ensuring":[0],"sustained":[1],"autonomy":[2],"in":[3,34,112],"unmanned":[4],"aerial":[5],"vehicles":[6],"(UAVs)":[7],"requires":[8],"robust":[9],"real-time":[10,104],"monitoring":[11,40],"of":[12,52,101,120],"critical":[13],"components":[14],"such":[15,115],"as":[16,50,65,116],"propellers.":[17,35,122],"Addressing":[18],"this":[19,21,131],"need,":[20],"study":[22],"introduces":[23],"an":[24,38,68,98],"emerging":[25,124],"lightweight":[26,79,125],"CNN-based":[27],"technology":[28],"for":[29,103],"noninvasive":[30,128],"acoustic":[31,39,129],"anomaly":[32,160],"detection":[33],"We":[36],"developed":[37],"methodology":[41],"that":[42,63],"captures":[43],"operational":[44],"UAV":[45,141,150],"sounds,":[46],"using":[47],"propeller-emitted":[48],"frequencies":[49],"indicators":[51],"structural":[53,135],"health.":[54],"Acoustic":[55],"signals":[56],"are":[57],"processed":[58],"into":[59],"2D":[60],"feature":[61],"maps":[62],"serve":[64],"input":[66],"to":[67],"optimized":[69],"and":[70,92,127,154],"computationally":[71],"efficient":[72],"convolutional":[73],"neural":[74],"network":[75],"(CNN)":[76],"architecture.":[77],"This":[78],"deep":[80],"learning":[81],"model":[82],"classifies":[83],"four":[84],"propeller":[85],"states:":[86],"intact,":[87],"minor":[88],"damage,":[89,91],"severe":[90],"imbalance.":[93],"The":[94],"experimental":[95],"results":[96],"demonstrate":[97],"average":[99],"accuracy":[100],"98%":[102],"fault":[105],"identification.":[106],"However,":[107],"the":[108,118],"approach":[109],"faced":[110],"challenges":[111],"finer-grained":[113],"classification,":[114],"quantifying":[117],"number":[119],"imbalanced":[121],"Using":[123],"CNNs":[126],"sensing,":[130],"method":[132],"enables":[133],"continuous":[134],"health":[136],"assessment":[137],"onboard":[138],"without":[139],"disrupting":[140],"operations.":[142],"It":[143],"represents":[144],"a":[145],"significant":[146],"advancement":[147],"towards":[148],"sustainable":[149],"autonomy,":[151],"enhancing":[152],"safety":[153],"reducing":[155],"maintenance":[156],"costs":[157],"through":[158],"early":[159],"detection.":[161]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-12-05T00:00:00"}
