{"id":"https://openalex.org/W4403535104","doi":"https://doi.org/10.1109/codit62066.2024.10708222","title":"Exploiting Related Sensor Measurements for Effective Unsupervised Learning-based Detection of Equipment Anomalies<sup>*</sup>","display_name":"Exploiting Related Sensor Measurements for Effective Unsupervised Learning-based Detection of Equipment Anomalies<sup>*</sup>","publication_year":2024,"publication_date":"2024-07-01","ids":{"openalex":"https://openalex.org/W4403535104","doi":"https://doi.org/10.1109/codit62066.2024.10708222"},"language":"en","primary_location":{"id":"doi:10.1109/codit62066.2024.10708222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/codit62066.2024.10708222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 10th International Conference on Control, Decision and Information Technologies (CoDIT)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5018743076","display_name":"Chieh\u2010Yu Chen","orcid":"https://orcid.org/0000-0001-8315-0781"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chieh-Yu Chen","raw_affiliation_strings":["National Taiwan University,Electrical Engineering Department,Taipei,Taiwan,10617"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University,Electrical Engineering Department,Taipei,Taiwan,10617","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089159973","display_name":"Shi\u2010Chung Chang","orcid":"https://orcid.org/0000-0001-7595-2485"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shi-Chung Chang","raw_affiliation_strings":["National Taiwan University,Electrical Engineering Department,Taipei,Taiwan,10617"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University,Electrical Engineering Department,Taipei,Taiwan,10617","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":0.3556,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56675815,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2182","last_page":"2187"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9488999843597412,"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":0.9488999843597412,"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":0.944100022315979,"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/unsupervised-learning","display_name":"Unsupervised learning","score":0.580359935760498},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5732195377349854},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.43652796745300293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40304774045944214}],"concepts":[{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.580359935760498},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5732195377349854},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.43652796745300293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40304774045944214}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/codit62066.2024.10708222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/codit62066.2024.10708222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 10th International Conference on Control, Decision and Information Technologies (CoDIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2100922564","https://openalex.org/W2918377632","https://openalex.org/W3081497074","https://openalex.org/W3090617142","https://openalex.org/W3190748826","https://openalex.org/W4206555898","https://openalex.org/W4280647411","https://openalex.org/W4281752626","https://openalex.org/W4318822164","https://openalex.org/W4323314880","https://openalex.org/W4385988699"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W4285233543","https://openalex.org/W4230838436"],"abstract_inverted_index":{"Unsupervised":[0],"learning-based":[1],"equipment":[2],"Anomaly":[3,30],"Detection":[4,31],"(AD)":[5],"has":[6,142],"become":[7],"increasingly":[8],"important":[9],"in":[10,17,67,193],"facilitating":[11],"proactive":[12],"yield":[13],"and":[14,25,46,60,162,180],"operations":[15],"management":[16],"smart":[18],"manufacturing.":[19],"The":[20,136],"authors":[21],"designed":[22],"a":[23,112,152,173,195],"Spectral":[24],"Time":[26],"Autoencoder":[27],"Learning":[28],"for":[29,120],"(STALAD)":[32],"framework":[33],"to":[34,64,77,85,129,191],"automate":[35],"AD":[36],"on":[37,182],"individual":[38],"sensory":[39],"data":[40,59],"items":[41],"by":[42],"integrating":[43],"normality":[44],"learning":[45],"hypothesis":[47],"testing.":[48],"Specifically,":[49],"STALAD":[50,71,192],"utilizes":[51],"error":[52,117,127,149],"sequences,":[53],"the":[54,57,61,80,92,131,139,169,199],"difference":[55],"between":[56],"given":[58,174],"learned":[62],"normality,":[63],"identify":[65],"anomalies":[66],"each":[68],"item.":[69],"Although":[70],"performs":[72],"well":[73],"without":[74],"resorting":[75],"much":[76],"knowledge":[78],"about":[79],"data,":[81],"its":[82],"testing":[83],"fails":[84],"consider":[86],"relations":[87],"among":[88],"sensor":[89],"measurements,":[90],"especially":[91],"simultaneity":[93,132],"of":[94,116,133,138,168,179],"anomaly":[95,121,134,158,197],"signals,":[96],"which":[97,124],"may":[98],"help":[99],"improve":[100],"detection":[101,122],"sensitivity":[102,190],"and/or":[103],"reduce":[104],"false":[105,175,201],"alarms.":[106],"In":[107],"this":[108],"paper,":[109],"we":[110],"design":[111,141],"novel":[113],"test":[114,153,170],"scheme":[115],"sequence":[118],"fusion":[119],"(MESFAD),":[123],"fuses":[125],"multiple":[126],"sequences":[128,150],"exploit":[130],"signals.":[135],"novelty":[137],"MESFAD":[140,187],"two":[143],"folds:":[144],"(i)":[145],"evenly":[146],"fusing":[147],"standardized":[148],"as":[151],"statistic":[154],"that":[155,186],"amplifies":[156],"simultaneous":[157],"signals":[159],"over":[160],"noises,":[161],"(ii)":[163],"probabilistic":[164],"approximation":[165],"model-based":[166],"setting":[167],"threshold":[171],"under":[172],"alarm":[176,202],"rate.":[177,203],"Analysis":[178],"experiments":[181],"two-item":[183],"cases":[184],"show":[185],"achieves":[188],"superior":[189],"detecting":[194],"shift-type":[196],"at":[198],"same":[200]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
