{"id":"https://openalex.org/W2996310699","doi":"https://doi.org/10.1109/snpd.2019.8935752","title":"Assets Predictive Maintenance Using Convolutional Neural Networks","display_name":"Assets Predictive Maintenance Using Convolutional Neural Networks","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2996310699","doi":"https://doi.org/10.1109/snpd.2019.8935752","mag":"2996310699"},"language":"en","primary_location":{"id":"doi:10.1109/snpd.2019.8935752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2019.8935752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","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/A5057741605","display_name":"Willamos Silva","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Willamos Silva","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Western University, London, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Western University, London, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083634004","display_name":"Miriam A. M. Capretz","orcid":"https://orcid.org/0000-0002-1380-971X"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Miriam Capretz","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Western University, London, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Western University, London, Canada","institution_ids":["https://openalex.org/I125749732"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5057741605"],"corresponding_institution_ids":["https://openalex.org/I125749732"],"apc_list":null,"apc_paid":null,"fwci":0.8098,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.77892786,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"59","last_page":"66"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14319","display_name":"Currency Recognition and Detection","score":0.9890999794006348,"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"}},"topics":[{"id":"https://openalex.org/T14319","display_name":"Currency Recognition and Detection","score":0.9890999794006348,"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"}},{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":0.986299991607666,"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/T13690","display_name":"Quality and Safety in Healthcare","score":0.9775000214576721,"subfield":{"id":"https://openalex.org/subfields/3607","display_name":"Medical Laboratory Technology"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7826892137527466},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7643208503723145},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6663551330566406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.642902672290802},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5631030201911926},{"id":"https://openalex.org/keywords/predictive-maintenance","display_name":"Predictive maintenance","score":0.5316040515899658},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5285875797271729},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5221303105354309},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5168788433074951},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4990413188934326},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4880017340183258},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4703139364719391},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4453592300415039},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36557281017303467},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34911805391311646},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09598177671432495}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7826892137527466},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7643208503723145},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6663551330566406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.642902672290802},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5631030201911926},{"id":"https://openalex.org/C70452415","wikidata":"https://www.wikidata.org/wiki/Q3182448","display_name":"Predictive maintenance","level":2,"score":0.5316040515899658},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5285875797271729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5221303105354309},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5168788433074951},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4990413188934326},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4880017340183258},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4703139364719391},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4453592300415039},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36557281017303467},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34911805391311646},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09598177671432495},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/snpd.2019.8935752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2019.8935752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1558305913","https://openalex.org/W1596717185","https://openalex.org/W1977177161","https://openalex.org/W1999393241","https://openalex.org/W2028418455","https://openalex.org/W2035855192","https://openalex.org/W2053186076","https://openalex.org/W2085537629","https://openalex.org/W2101713460","https://openalex.org/W2120841219","https://openalex.org/W2163605009","https://openalex.org/W2167101736","https://openalex.org/W2523916473","https://openalex.org/W2524620548","https://openalex.org/W2562473339","https://openalex.org/W2594434602","https://openalex.org/W2735895797","https://openalex.org/W2738359832","https://openalex.org/W2766440025","https://openalex.org/W2766809745","https://openalex.org/W2768641377","https://openalex.org/W2804522644","https://openalex.org/W2888844977","https://openalex.org/W2911964244","https://openalex.org/W2919115771","https://openalex.org/W2963866024","https://openalex.org/W6675357634","https://openalex.org/W6684191040","https://openalex.org/W6746269285"],"related_works":["https://openalex.org/W2889302474","https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456"],"abstract_inverted_index":{"Predictive":[0],"Maintenance":[1],"(PdM)":[2],"performs":[3],"maintenance":[4,70],"based":[5],"on":[6],"the":[7,94,101,139,144,149,171,184,189],"asset's":[8],"health":[9],"status":[10],"indicators.":[11],"Sensors":[12],"can":[13],"measure":[14],"an":[15,23,40,81],"unusual":[16,41],"pattern":[17,42],"of":[18,43,56,96,146,183],"these":[19,44],"indicators,":[20],"such":[21],"as":[22,177,179],"increased":[24],"motor's":[25],"vibration":[26],"level":[27],"or":[28],"higher":[29],"energy":[30],"consumption,":[31],"and,":[32],"in":[33,125],"most":[34],"cases,":[35],"failures":[36],"are":[37],"preceded":[38],"by":[39,138,170],"measurements.":[45],"Convolutional":[46],"Neural":[47],"Network":[48],"(CNN)":[49],"is":[50,89],"a":[51,63,73,115,126,132],"Machine":[52],"Learning":[53],"technique":[54],"capable":[55],"extracting":[57],"data":[58,79,86,121,151],"representation.":[59],"This":[60],"paper":[61],"presents":[62],"CNN":[64,97,147],"framework":[65,103,141,173],"to":[66,75,92,131],"tackle":[67],"assets":[68],"predictive":[69],"problem":[71],"and":[72,129,164,186],"method":[74,153],"transform":[76],"1-dimensional":[77],"(1-D)":[78],"into":[80],"image-like":[82,127],"representation":[83,128],"(2-D).":[84],"A":[85],"transformation":[87,152],"step":[88],"very":[90],"important":[91],"make":[93],"use":[95],"feasible.":[98],"To":[99],"evaluate":[100],"proposed":[102,150],"two":[104],"datasets":[105,185],"were":[106],"obtained":[107],"from":[108,114],"fans,":[109],"with":[110,148],"distinct":[111],"electrical":[112],"pattern,":[113],"building":[116],"at":[117],"Western":[118],"University.":[119],"The":[120,135,167],"was":[122],"preprocessed,":[123],"transformed":[124],"fed":[130],"tuned":[133],"classifier.":[134],"results":[136],"presented":[137],"CNN-PdM":[140,172],"showed":[142],"that":[143],"combination":[145],"outperformed":[154],"traditional":[155],"machine":[156],"learning":[157],"techniques":[158],"(Random":[159],"Forest,":[160],"Support":[161],"Vector":[162],"Machine,":[163],"Multi-Layer":[165],"Perceptron).":[166],"model":[168],"created":[169],"achieved":[174],"accuracy":[175],"rates":[176],"high":[178],"98%":[180],"for":[181,188],"one":[182],"95%":[187],"other.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
