{"id":"https://openalex.org/W4415398681","doi":"https://doi.org/10.1109/etfa65518.2025.11205807","title":"Unsupervised Anomaly Detection in Industrial Machines supported by Vibration analysis Under Data Scarcity Constraints","display_name":"Unsupervised Anomaly Detection in Industrial Machines supported by Vibration analysis Under Data Scarcity Constraints","publication_year":2025,"publication_date":"2025-09-09","ids":{"openalex":"https://openalex.org/W4415398681","doi":"https://doi.org/10.1109/etfa65518.2025.11205807"},"language":null,"primary_location":{"id":"doi:10.1109/etfa65518.2025.11205807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa65518.2025.11205807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)","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/A5005013584","display_name":"Pedro Torres","orcid":"https://orcid.org/0000-0003-4835-5022"},"institutions":[{"id":"https://openalex.org/I144926016","display_name":"Polytechnic Institute of Castelo Branco","ror":"https://ror.org/004s18446","country_code":"PT","type":"education","lineage":["https://openalex.org/I144926016"]}],"countries":["PT"],"is_corresponding":true,"raw_author_name":"Pedro M. B. Torres","raw_affiliation_strings":["FEUP - Porto Polytechnic University of Castelo Branco,SYSTEC &#x0026; ARISE,Castelo Branco,Portugal"],"affiliations":[{"raw_affiliation_string":"FEUP - Porto Polytechnic University of Castelo Branco,SYSTEC &#x0026; ARISE,Castelo Branco,Portugal","institution_ids":["https://openalex.org/I144926016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078038604","display_name":"Geoffrey Spencer","orcid":"https://orcid.org/0000-0002-9945-9916"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Geoffrey O. T. Spencer","raw_affiliation_strings":["FEUP,SYSTEC,Porto,Portugal"],"affiliations":[{"raw_affiliation_string":"FEUP,SYSTEC,Porto,Portugal","institution_ids":["https://openalex.org/I182534213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079184870","display_name":"Anderson Alves Esteves","orcid":"https://orcid.org/0000-0003-1479-3323"},"institutions":[{"id":"https://openalex.org/I144926016","display_name":"Polytechnic Institute of Castelo Branco","ror":"https://ror.org/004s18446","country_code":"PT","type":"education","lineage":["https://openalex.org/I144926016"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Arthur Esteves","raw_affiliation_strings":["Polytechnic University of Castelo Branco,School of Technology,Castelo Branco,Portugal"],"affiliations":[{"raw_affiliation_string":"Polytechnic University of Castelo Branco,School of Technology,Castelo Branco,Portugal","institution_ids":["https://openalex.org/I144926016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044672578","display_name":"Fernando Sousa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165287","display_name":"Companhia de Equipamentos Industriais","ror":"https://ror.org/05c2m7279","country_code":"PT","type":"company","lineage":["https://openalex.org/I4210165287"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Fernando Sousa","raw_affiliation_strings":["CEI Companhia de Equipamentos Industriais, Lda,Technical Department,S&#x00E3;o Jo&#x00E3;o da Madeira,Portugal"],"affiliations":[{"raw_affiliation_string":"CEI Companhia de Equipamentos Industriais, Lda,Technical Department,S&#x00E3;o Jo&#x00E3;o da Madeira,Portugal","institution_ids":["https://openalex.org/I4210165287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068000962","display_name":"Filomena Pereira","orcid":"https://orcid.org/0000-0003-3421-7833"},"institutions":[{"id":"https://openalex.org/I4210091074","display_name":"Centro Tecnol\u00f3gico do Cal\u00e7ado de Portugal","ror":"https://ror.org/00beq0325","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210091074"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Fernando J. G. Pereira","raw_affiliation_strings":["INOCAM,Technical Department,S&#x00E3;o Jo&#x00E3;o da Madeira,Portugal"],"affiliations":[{"raw_affiliation_string":"INOCAM,Technical Department,S&#x00E3;o Jo&#x00E3;o da Madeira,Portugal","institution_ids":["https://openalex.org/I4210091074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028850963","display_name":"Rui Guerreiro","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091074","display_name":"Centro Tecnol\u00f3gico do Cal\u00e7ado de Portugal","ror":"https://ror.org/00beq0325","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210091074"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Rui M. L. Guerreiro","raw_affiliation_strings":["INOCAM,Technical Department,S&#x00E3;o Jo&#x00E3;o da Madeira,Portugal"],"affiliations":[{"raw_affiliation_string":"INOCAM,Technical Department,S&#x00E3;o Jo&#x00E3;o da Madeira,Portugal","institution_ids":["https://openalex.org/I4210091074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5005013584"],"corresponding_institution_ids":["https://openalex.org/I144926016"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16547632,"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":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9951000213623047,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9951000213623047,"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":0.9918000102043152,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.910099983215332,"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/anomaly-detection","display_name":"Anomaly detection","score":0.7419000267982483},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5432000160217285},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.5264999866485596},{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"Condition monitoring","score":0.4869000017642975},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.48260000348091125},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.47999998927116394},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.47929999232292175},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4708000123500824},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.450300008058548}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7419000267982483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5884000062942505},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5536999702453613},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5432000160217285},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.5264999866485596},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5242000222206116},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.4869000017642975},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.47999998927116394},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.47929999232292175},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4708000123500824},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.450300008058548},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41370001435279846},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3896999955177307},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3894999921321869},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3806000053882599},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C70452415","wikidata":"https://www.wikidata.org/wiki/Q3182448","display_name":"Predictive maintenance","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3264000117778778},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3237999975681305},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3230000138282776},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3176000118255615},{"id":"https://openalex.org/C2984282874","wikidata":"https://www.wikidata.org/wiki/Q10952243","display_name":"Industrial equipment","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C5941749","wikidata":"https://www.wikidata.org/wiki/Q19768","display_name":"Machine tool","level":2,"score":0.30970001220703125},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C144171764","wikidata":"https://www.wikidata.org/wiki/Q48103","display_name":"Torque","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C17281054","wikidata":"https://www.wikidata.org/wiki/Q193466","display_name":"Rotor (electric)","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/etfa65518.2025.11205807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa65518.2025.11205807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,149],"integration":[1],"of":[2,5,16,26,41,60,66,88,99,114,127,137,158],"the":[3,14,39,58,84,112,118,128,134,138,156,169],"use":[4,123],"Artificial":[6],"Intelligence":[7],"(AI)":[8],"in":[9,37,53,62,155,180],"industrial":[10,42,55,181],"environments":[11],"often":[12],"faces":[13],"lack":[15,25],"labeled":[17,159],"data,":[18,82,160],"as":[19,21,125],"well":[20],"historical":[22],"records.":[23],"This":[24,48],"information":[27],"becomes":[28],"a":[29,63,174],"problem":[30],"when":[31],"implementing":[32],"predictive":[33],"maintenance":[34],"solutions,":[35],"particularly":[36],"monitoring":[38],"condition":[40],"machines":[43,182],"and":[44,86,140,172],"automatic":[45],"fault":[46],"detection.":[47],"work":[49],"addresses":[50],"this":[51],"issue":[52],"an":[54,67,89],"scenario,":[56],"through":[57,80,183],"analysis":[59,109],"vibrations":[61],"spindle":[64],"motor":[65],"ornamental":[68],"stone":[69],"cutting":[70],"machine.":[71],"Unsupervised":[72],"learning":[73],"techniques":[74],"are":[75],"explored":[76],"for":[77,177],"anomaly":[78,178],"detection":[79,179],"vibration":[81,184],"using":[83],"training":[85],"implementation":[87],"LSTM":[90],"(Long":[91],"Short-Term":[92],"Memory)":[93],"Autoencoder":[94],"model.":[95],"Datasets":[96],"consist":[97],"only":[98],"unlabeled":[100],"accelerometer":[101],"signals":[102],"acquired":[103],"during":[104],"normal":[105,135],"machine":[106,139,170],"operation.":[107],"An":[108],"based":[110],"on":[111],"extraction":[113],"statistical":[115],"features":[116],"from":[117,168],"signal":[119],"is":[120,162],"adopted":[121],"to":[122,132,146,164],"them":[124],"inputs":[126],"Machine":[129],"Learning":[130],"algorithm,":[131],"learn":[133],"behavior":[136],"detect":[141],"deviations":[142],"that":[143,153],"may":[144],"correspond":[145],"potential":[147],"anomalies.":[148],"experimental":[150],"results":[151],"show":[152],"even":[154],"absence":[157],"it":[161],"possible":[163],"extract":[165],"meaningful":[166],"insights":[167],"state":[171],"establish":[173],"practical":[175],"pipeline":[176],"analysis.":[185]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-22T00:00:00"}
