{"id":"https://openalex.org/W3116945867","doi":"https://doi.org/10.1109/tcyb.2020.3038832","title":"Intelligent Fault Diagnosis for Chemical Processes Using Deep Learning Multimodel Fusion","display_name":"Intelligent Fault Diagnosis for Chemical Processes Using Deep Learning Multimodel Fusion","publication_year":2020,"publication_date":"2020-12-30","ids":{"openalex":"https://openalex.org/W3116945867","doi":"https://doi.org/10.1109/tcyb.2020.3038832","mag":"3116945867","pmid":"https://pubmed.ncbi.nlm.nih.gov/33378269"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2020.3038832","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2020.3038832","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100332720","display_name":"Nan Wang","orcid":"https://orcid.org/0000-0001-8786-7923"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nan Wang","raw_affiliation_strings":["Information and Control Institute, Hangzhou Dianzi University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Information and Control Institute, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077651830","display_name":"Fan Yang","orcid":"https://orcid.org/0000-0002-0254-9000"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Yang","raw_affiliation_strings":["Information and Control Institute, Hangzhou Dianzi University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Information and Control Institute, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102910833","display_name":"Ridong Zhang","orcid":"https://orcid.org/0000-0002-9822-5384"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ridong Zhang","raw_affiliation_strings":["Information and Control Institute, Hangzhou Dianzi University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Information and Control Institute, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002154840","display_name":"Furong Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Furong Gao","raw_affiliation_strings":["Chemical and Biological Engineering Department, Hong Kong University of Science and Technology, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Chemical and Biological Engineering Department, Hong Kong University of Science and Technology, Hong Kong","institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100332720"],"corresponding_institution_ids":["https://openalex.org/I50760025"],"apc_list":null,"apc_paid":null,"fwci":5.0575,"has_fulltext":false,"cited_by_count":96,"citation_normalized_percentile":{"value":0.95939196,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"52","issue":"7","first_page":"7121","last_page":"7135"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9988999962806702,"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":0.9988999962806702,"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/T12282","display_name":"Mineral Processing and Grinding","score":0.9805999994277954,"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/T13891","display_name":"Engineering Diagnostics and Reliability","score":0.9599999785423279,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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":0.7757810354232788},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.772771418094635},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7487181425094604},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6653277277946472},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6094319820404053},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5901269912719727},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5261228680610657},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5112307071685791},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5106173157691956},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4894053041934967},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4525522291660309},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4491342604160309}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7757810354232788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.772771418094635},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7487181425094604},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6653277277946472},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6094319820404053},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5901269912719727},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5261228680610657},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5112307071685791},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5106173157691956},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4894053041934967},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4525522291660309},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4491342604160309},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"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":"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},{"descriptor_ui":"D055598","descriptor_name":"Chemical Phenomena","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055598","descriptor_name":"Chemical Phenomena","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055598","descriptor_name":"Chemical Phenomena","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1109/tcyb.2020.3038832","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2020.3038832","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cybernetics","raw_type":"journal-article"},{"id":"pmid:33378269","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33378269","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":"IEEE transactions on cybernetics","raw_type":null},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-109008","is_oa":false,"landing_page_url":"http://www.scopus.com/record/display.url?eid=2-s2.0-85099097512&origin=inward","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:repository.ust.hk:1783.1-109008","is_oa":false,"landing_page_url":"http://repository.ust.hk/ir/Record/1783.1-109008","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.550000011920929,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1870381889","https://openalex.org/W1932847118","https://openalex.org/W1974401242","https://openalex.org/W1975514583","https://openalex.org/W1985994459","https://openalex.org/W1997177391","https://openalex.org/W2017925686","https://openalex.org/W2022466535","https://openalex.org/W2063922127","https://openalex.org/W2072315088","https://openalex.org/W2073178151","https://openalex.org/W2089146074","https://openalex.org/W2093624953","https://openalex.org/W2095705004","https://openalex.org/W2107878631","https://openalex.org/W2136485962","https://openalex.org/W2136848157","https://openalex.org/W2296077894","https://openalex.org/W2296451705","https://openalex.org/W2341973567","https://openalex.org/W2473060649","https://openalex.org/W2493697924","https://openalex.org/W2509171187","https://openalex.org/W2556345765","https://openalex.org/W2580840020","https://openalex.org/W2586262374","https://openalex.org/W2589808763","https://openalex.org/W2612554669","https://openalex.org/W2734669076","https://openalex.org/W2768753204","https://openalex.org/W2774636206","https://openalex.org/W2780628352","https://openalex.org/W2788805965","https://openalex.org/W2795765414","https://openalex.org/W2796942168","https://openalex.org/W2801396593","https://openalex.org/W2804652951","https://openalex.org/W2908628397","https://openalex.org/W2914488306","https://openalex.org/W2919115771","https://openalex.org/W2920714358","https://openalex.org/W2995524811","https://openalex.org/W6674330103"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2082756648","https://openalex.org/W3194278305","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Deep":[0],"learning":[1,16,92,99,228],"technology":[2],"has":[3,45,146],"been":[4],"widely":[5],"used":[6],"in":[7,48],"fault":[8,40,87,229],"diagnosis":[9,41,51,88,100,140,176,230],"for":[10,131,175,211,236],"chemical":[11,201],"processes.":[12],"However,":[13],"most":[14],"deep":[15,91,98,227],"technologies":[17],"currently":[18],"adopted":[19],"only":[20],"use":[21],"a":[22,27,62,86,159,199],"single":[23,63],"network":[24,29,112,185],"stack":[25,30],"or":[26,67],"certain":[28],"with":[31,38,232],"multilayer":[32],"perceptron":[33],"(MLP)":[34],"behind":[35],"it.":[36],"Compared":[37],"traditional":[39],"technologies,":[42],"this":[43,83,102,221],"method":[44,89,103,170,222],"made":[46],"progress":[47],"both":[49,187],"the":[50,58,65,71,74,129,139,150,163,179,184,194,218],"accuracy":[52,66],"and":[53,109,124,135,137,156,189,203],"speed,":[54],"but":[55],"due":[56],"to":[57,73,79,114,225],"limited":[59],"performance":[60,219],"of":[61,165,220],"network,":[64],"speed":[68],"cannot":[69],"meet":[70],"requirements":[72],"greatest":[75],"extent.":[76],"In":[77],"order":[78],"overcome":[80],"such":[81,177],"problems,":[82],"article":[84],"proposes":[85],"using":[90],"multimodel":[93],"fusion.":[94],"Different":[95],"from":[96],"previous":[97],"methods,":[101],"uses":[104],"long":[105],"short-term":[106],"memory":[107,148],"(LSTM)":[108],"convolutional":[110],"neural":[111],"(CNN)":[113],"extract":[115],"features":[116,120,152,180],"separately.":[117],"The":[118,168],"extracted":[119,151,182],"are":[121,209],"then":[122],"fused":[123],"MLP":[125],"is":[126,215,223],"taken":[127,210],"as":[128],"input":[130],"further":[132],"feature":[133,238],"compression":[134],"extraction,":[136],"finally":[138,181],"results":[141],"will":[142],"be":[143],"obtained.":[144],"LSTM":[145],"long-term":[147],"capabilities,":[149],"have":[153,158,186],"temporal":[154,190],"characteristics,":[155,191],"CNNs":[157],"good":[160],"effect":[161],"on":[162],"extraction":[164],"spatial":[166,188],"features.":[167],"proposed":[169],"integrates":[171],"these":[172],"two":[173],"aspects":[174],"that":[178,217],"by":[183],"thereby":[192],"improving":[193],"network's":[195],"diagnostic":[196],"performance.":[197],"Finally,":[198],"TE":[200],"process":[202,208],"an":[204],"industrial":[205],"coking":[206],"furnace":[207],"simulation":[212],"testing.":[213],"It":[214],"proved":[216],"superior":[224],"existing":[226],"methods":[231],"simple":[233],"sequential":[234],"stacking":[235],"unilateral":[237],"extraction.":[239]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":25},{"year":2024,"cited_by_count":33},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":5}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
