{"id":"https://openalex.org/W3133831663","doi":"https://doi.org/10.1145/3448823.3448863","title":"Automated Condition Monitoring Using Artificial Intelligence","display_name":"Automated Condition Monitoring Using Artificial Intelligence","publication_year":2020,"publication_date":"2020-12-09","ids":{"openalex":"https://openalex.org/W3133831663","doi":"https://doi.org/10.1145/3448823.3448863","mag":"3133831663"},"language":"en","primary_location":{"id":"doi:10.1145/3448823.3448863","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3448823.3448863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing","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/A5088632284","display_name":"Ieuan Ll. Griffiths","orcid":null},"institutions":[{"id":"https://openalex.org/I128993996","display_name":"University of South Wales","ror":"https://ror.org/02mzn7s88","country_code":"GB","type":"education","lineage":["https://openalex.org/I128993996"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ieuan Griffiths","raw_affiliation_strings":["University of South Wales, Treforest, Pontypridd, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Wales, Treforest, Pontypridd, UK","institution_ids":["https://openalex.org/I128993996"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5088632284"],"corresponding_institution_ids":["https://openalex.org/I128993996"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.20379709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"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":0.9983999729156494,"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":0.9983999729156494,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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":0.9900000095367432,"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/computer-science","display_name":"Computer science","score":0.7356609106063843},{"id":"https://openalex.org/keywords/predictive-maintenance","display_name":"Predictive maintenance","score":0.56833416223526},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5469019412994385},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5067198872566223},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4733341336250305},{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"Condition monitoring","score":0.45271337032318115},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.44381415843963623},{"id":"https://openalex.org/keywords/preventive-maintenance","display_name":"Preventive maintenance","score":0.4378660023212433},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.303083211183548},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16810834407806396}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7356609106063843},{"id":"https://openalex.org/C70452415","wikidata":"https://www.wikidata.org/wiki/Q3182448","display_name":"Predictive maintenance","level":2,"score":0.56833416223526},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5469019412994385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5067198872566223},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4733341336250305},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.45271337032318115},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.44381415843963623},{"id":"https://openalex.org/C24090081","wikidata":"https://www.wikidata.org/wiki/Q1043452","display_name":"Preventive maintenance","level":2,"score":0.4378660023212433},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.303083211183548},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16810834407806396},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3448823.3448863","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3448823.3448863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1595782850","https://openalex.org/W2139399084","https://openalex.org/W2571645497","https://openalex.org/W2727721835","https://openalex.org/W2739846485","https://openalex.org/W2740924709","https://openalex.org/W2768988016","https://openalex.org/W2834866711","https://openalex.org/W4388311501"],"related_works":["https://openalex.org/W4214827973","https://openalex.org/W23403803","https://openalex.org/W2063020871","https://openalex.org/W2315243270","https://openalex.org/W3006925589","https://openalex.org/W4231557335","https://openalex.org/W1969617929","https://openalex.org/W2394158014","https://openalex.org/W3159422131","https://openalex.org/W4210572926"],"abstract_inverted_index":{"Machine":[0],"maintenance":[1,19,63],"is":[2,21,123],"a":[3,17,30,41,78,86,95,107,170],"major":[4],"part":[5],"of":[6,44,67,125,146,166],"total":[7],"operating":[8,70,97,177],"costs":[9],"for":[10],"manufacturing":[11],"and":[12,60,72,93,118,142],"production":[13],"plants,":[14],"hence,":[15],"having":[16],"cost-effective":[18],"strategy":[20],"key":[22],"to":[23,75,128],"success.":[24],"Most":[25],"standard":[26],"solutions":[27],"operate":[28],"on":[29,155],"time-driven":[31],"approach":[32],"where":[33],"repairs":[34],"or":[35,103],"replacements":[36],"are":[37,144],"carried":[38],"out":[39],"after":[40],"given":[42],"amount":[43],"time.":[45],"This":[46,83],"results":[47],"in":[48,56,113,149,179],"healthy":[49],"machines":[50,96,131],"being":[51,126,147],"replaced":[52],"unnecessarily":[53],"incurring":[54],"losses":[55],"both":[57],"time,":[58],"resource,":[59],"parts.":[61],"Predictive":[62],"utilises":[64],"sensors":[65],"capable":[66,124,145],"collecting":[68],"real-time":[69,171],"data":[71,172],"analytical":[73],"techniques":[74],"predict":[76],"when":[77],"machine":[79],"will":[80],"require":[81],"maintenance.":[82],"research":[84],"develops":[85],"vibration":[87],"analysis":[88,102],"tool":[89,122,168],"that":[90,136,174],"can":[91,175],"detect":[92],"differentiate":[94],"conditions":[98,178],"without":[99,132],"any":[100],"human":[101],"intervention":[104],"demonstrated":[105],"via":[106],"case":[108,156],"study.":[109],"By":[110],"using":[111,139],"spectrograms":[112],"conjunction":[114],"with":[115],"image":[116],"recognition":[117],"unsupervised":[119,151],"learning,":[120],"the":[121,164],"applied":[127],"many":[129],"different":[130],"modification.":[133],"Results":[134],"show":[135],"features":[137],"extracted":[138],"convolutional":[140],"auto-encoding":[141],"t-SNE,":[143],"clustered":[148],"an":[150],"manner":[152],"accurately":[153],"based":[154],"study":[157],"test":[158],"conditions.":[159],"Future":[160],"work":[161],"looks":[162],"at":[163],"application":[165],"this":[167],"into":[169],"stream":[173],"determine":[176],"real-time.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}