{"id":"https://openalex.org/W3133607401","doi":"https://doi.org/10.1155/2021/6612342","title":"A Fault Prediction and Cause Identification Approach in Complex Industrial Processes Based on Deep Learning","display_name":"A Fault Prediction and Cause Identification Approach in Complex Industrial Processes Based on Deep Learning","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3133607401","doi":"https://doi.org/10.1155/2021/6612342","mag":"3133607401","pmid":"https://pubmed.ncbi.nlm.nih.gov/33747072"},"language":"en","primary_location":{"id":"doi:10.1155/2021/6612342","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/6612342","pdf_url":"https://downloads.hindawi.com/journals/cin/2021/6612342.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/cin/2021/6612342.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100704267","display_name":"Yao Li","orcid":"https://orcid.org/0000-0003-0974-6549"},"institutions":[{"id":"https://openalex.org/I87182695","display_name":"Universidad del Noreste","ror":"https://ror.org/02ahky613","country_code":"MX","type":"education","lineage":["https://openalex.org/I87182695"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN","MX"],"is_corresponding":true,"raw_author_name":"Yao Li","raw_affiliation_strings":["School of Computer Science and Engineering, Northeastern University, Liao Ning, China","School of Computer Science and Engineering, Northeastern University, Liao Ning"],"raw_orcid":"https://orcid.org/0000-0003-0974-6549","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Liao Ning, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Liao Ning","institution_ids":["https://openalex.org/I87182695"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100704267"],"corresponding_institution_ids":["https://openalex.org/I87182695","https://openalex.org/I9224756"],"apc_list":{"value":2100,"currency":"USD","value_usd":2100},"apc_paid":{"value":2100,"currency":"USD","value_usd":2100},"fwci":2.3592,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.88292016,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2021","issue":"1","first_page":"6612342","last_page":"6612342"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9990000128746033,"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":0.9897000193595886,"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/T12282","display_name":"Mineral Processing and Grinding","score":0.9778000116348267,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6761382818222046},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6124610900878906},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5954560041427612},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5686455368995667},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5219427943229675},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4575693905353546},{"id":"https://openalex.org/keywords/seismology","display_name":"Seismology","score":0.07233238220214844},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.06688699126243591}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6761382818222046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6124610900878906},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5954560041427612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5686455368995667},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5219427943229675},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4575693905353546},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.07233238220214844},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.06688699126243591},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1155/2021/6612342","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/6612342","pdf_url":"https://downloads.hindawi.com/journals/cin/2021/6612342.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},{"id":"pmid:33747072","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33747072","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational intelligence and neuroscience","raw_type":null},{"id":"pmh:oai:doaj.org/article:d75554010c3547fca558699ce2f423c0","is_oa":true,"landing_page_url":"https://doaj.org/article/d75554010c3547fca558699ce2f423c0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computational Intelligence and Neuroscience, Vol 2021 (2021)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:7954619","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7954619","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Comput Intell Neurosci","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1155/2021/6612342","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/6612342","pdf_url":"https://downloads.hindawi.com/journals/cin/2021/6612342.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4699999988079071}],"awards":[{"id":"https://openalex.org/G8807121210","display_name":null,"funder_award_id":"61772122","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3133607401.pdf","grobid_xml":"https://content.openalex.org/works/W3133607401.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W61851215","https://openalex.org/W1592847587","https://openalex.org/W1902237438","https://openalex.org/W1965875070","https://openalex.org/W2005530589","https://openalex.org/W2010001505","https://openalex.org/W2023000862","https://openalex.org/W2038394577","https://openalex.org/W2052828853","https://openalex.org/W2064675550","https://openalex.org/W2104167780","https://openalex.org/W2123585936","https://openalex.org/W2143288231","https://openalex.org/W2207849498","https://openalex.org/W2267186426","https://openalex.org/W2413794162","https://openalex.org/W2589808763","https://openalex.org/W2608089442","https://openalex.org/W2737725206","https://openalex.org/W2767087007","https://openalex.org/W2767547753","https://openalex.org/W2767547957","https://openalex.org/W2769355916","https://openalex.org/W2791139105","https://openalex.org/W2794081072","https://openalex.org/W2810084952","https://openalex.org/W2884001105","https://openalex.org/W2931273669","https://openalex.org/W2964248614","https://openalex.org/W2969262604","https://openalex.org/W2973942754","https://openalex.org/W2981386789","https://openalex.org/W2981552608","https://openalex.org/W3009961868","https://openalex.org/W3025806395","https://openalex.org/W3040708579","https://openalex.org/W3119945407"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W4321369474","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3046775127","https://openalex.org/W3082895349"],"abstract_inverted_index":{"Faults":[0],"occurring":[1],"in":[2,39,108,131,155,188,232],"the":[3,11,19,36,40,73,87,101,115,120,142,162,185,189,193,198,203,208,217,233,241,248,254],"production":[4,28,88],"line":[5,29],"can":[6,21,30,176,201,213,251],"cause":[7,135,218,257],"many":[8],"losses.":[9,25],"Predicting":[10],"fault":[12,132,150,229],"events":[13],"before":[14],"they":[15],"occur":[16],"or":[17],"identifying":[18],"causes":[20],"effectively":[22],"reduce":[23],"such":[24],"A":[26],"modern":[27],"provide":[31],"enough":[32],"data":[33,80,166],"to":[34,71,86,112,114,119],"solve":[35,72],"problem.":[37,74],"However,":[38],"face":[41],"of":[42,139,149,219],"complex":[43],"industrial":[44],"processes,":[45],"this":[46,57,156],"problem":[47],"will":[48],"become":[49],"very":[50],"difficult":[51],"depending":[52],"on":[53,65],"traditional":[54,94,140],"methods.":[55],"In":[56],"paper,":[58],"we":[59,76,99],"propose":[60],"a":[61,66,82,147,168,173],"new":[62],"approach":[63,153,223,242],"based":[64],"deep":[67],"learning":[68],"(DL)":[69],"algorithm":[70,128,200],"First,":[75],"regard":[77],"these":[78],"process":[79],"as":[81,146,167],"spatial":[83,121,169],"sequence":[84,148,170,175],"according":[85],"process,":[89],"which":[90],"is":[91,129,144,224],"different":[92],"from":[93],"time":[95,174],"series":[96],"data.":[97,210],"Second,":[98],"improve":[100,181],"long":[102],"short-term":[103],"memory":[104],"(LSTM)":[105],"neural":[106,191],"network":[107],"an":[109,124],"encoder-decoder":[110],"model":[111],"adapt":[113],"branch":[116],"structure,":[117],"corresponding":[118],"sequence.":[122],"Meanwhile,":[123],"attention":[125],"mechanism":[126],"(AM)":[127],"used":[130],"detection":[133],"and":[134,180,207,247],"identification.":[136],"Third,":[137],"instead":[138],"biclassification,":[141],"output":[143],"defined":[145],"types.":[151],"The":[152,221],"proposed":[154,222],"article":[157],"has":[158,243],"two":[159],"advantages.":[160],"On":[161,184],"one":[163],"hand,":[164,187],"treating":[165],"rather":[171],"than":[172],"overcome":[177],"multidimensional":[178],"problems":[179],"prediction":[182,245],"accuracy.":[183],"other":[186],"trained":[190],"network,":[192],"weight":[194,249],"vectors":[195],"generated":[196],"by":[197],"AM":[199],"represent":[202],"correlation":[204,212],"between":[205],"faults":[206],"input":[209],"This":[211],"help":[214],"engineers":[215],"identify":[216],"faults.":[220,258],"compared":[225],"with":[226],"some":[227],"well-developed":[228],"diagnosing":[230],"methods":[231],"Tennessee":[234],"Eastman":[235],"process.":[236],"Experimental":[237],"results":[238],"show":[239],"that":[240,256],"higher":[244],"accuracy,":[246],"vector":[250],"accurately":[252],"label":[253],"factors":[255]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-24T08:33:08.758527","created_date":"2025-10-10T00:00:00"}