{"id":"https://openalex.org/W3126794061","doi":"https://doi.org/10.1109/tcyb.2021.3050398","title":"MoniNet With Concurrent Analytics of Temporal and Spatial Information for Fault Detection in Industrial Processes","display_name":"MoniNet With Concurrent Analytics of Temporal and Spatial Information for Fault Detection in Industrial Processes","publication_year":2021,"publication_date":"2021-02-08","ids":{"openalex":"https://openalex.org/W3126794061","doi":"https://doi.org/10.1109/tcyb.2021.3050398","mag":"3126794061","pmid":"https://pubmed.ncbi.nlm.nih.gov/33544684"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2021.3050398","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2021.3050398","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/A5006722493","display_name":"Wanke Yu","orcid":"https://orcid.org/0000-0002-3927-5656"},"institutions":[{"id":"https://openalex.org/I4391767838","display_name":"State Key Laboratory of Industrial Control Technology","ror":"https://ror.org/03a33a786","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767838","https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wanke Yu","raw_affiliation_strings":["State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4391767838"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038929132","display_name":"Chunhui Zhao","orcid":"https://orcid.org/0000-0002-0254-5763"},"institutions":[{"id":"https://openalex.org/I4391767838","display_name":"State Key Laboratory of Industrial Control Technology","ror":"https://ror.org/03a33a786","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767838","https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhui Zhao","raw_affiliation_strings":["State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4391767838"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100432851","display_name":"Biao Huang","orcid":"https://orcid.org/0000-0001-9082-2216"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Biao Huang","raw_affiliation_strings":["Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Canada","institution_ids":["https://openalex.org/I154425047"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5006722493"],"corresponding_institution_ids":["https://openalex.org/I4391767838"],"apc_list":null,"apc_paid":null,"fwci":11.9257,"has_fulltext":false,"cited_by_count":104,"citation_normalized_percentile":{"value":0.99112882,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"52","issue":"8","first_page":"8340","last_page":"8351"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9998999834060669,"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":0.9998999834060669,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9763000011444092,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.974399983882904,"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/computer-science","display_name":"Computer science","score":0.768345057964325},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6337696313858032},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6304745674133301},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.6288092732429504},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6074139475822449},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.5811294317245483},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5404840707778931},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.46714138984680176},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.4584055244922638},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.4520461857318878},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.415638267993927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4109093248844147},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3609378933906555},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.34423524141311646},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3182351589202881},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.10318711400032043},{"id":"https://openalex.org/keywords/actuator","display_name":"Actuator","score":0.09374454617500305}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.768345057964325},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6337696313858032},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6304745674133301},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.6288092732429504},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6074139475822449},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.5811294317245483},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5404840707778931},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.46714138984680176},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.4584055244922638},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.4520461857318878},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.415638267993927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4109093248844147},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3609378933906555},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34423524141311646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3182351589202881},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.10318711400032043},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.09374454617500305},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","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":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2021.3050398","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2021.3050398","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:33544684","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33544684","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}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6100000143051147}],"awards":[{"id":"https://openalex.org/G623490099","display_name":null,"funder_award_id":"U1709211","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1587559447","https://openalex.org/W1616262590","https://openalex.org/W1870381889","https://openalex.org/W1972738875","https://openalex.org/W1981586857","https://openalex.org/W1987583608","https://openalex.org/W1988581389","https://openalex.org/W1994505190","https://openalex.org/W2001619934","https://openalex.org/W2003516238","https://openalex.org/W2004186751","https://openalex.org/W2033228602","https://openalex.org/W2051940462","https://openalex.org/W2066102264","https://openalex.org/W2072405524","https://openalex.org/W2077791644","https://openalex.org/W2100495367","https://openalex.org/W2111637385","https://openalex.org/W2123649031","https://openalex.org/W2141224535","https://openalex.org/W2142704389","https://openalex.org/W2169347809","https://openalex.org/W2344734818","https://openalex.org/W2473060649","https://openalex.org/W2511461628","https://openalex.org/W2567190712","https://openalex.org/W2626923521","https://openalex.org/W2751584934","https://openalex.org/W2774636206","https://openalex.org/W2775523681","https://openalex.org/W2788518677","https://openalex.org/W2789634333","https://openalex.org/W2795891046","https://openalex.org/W2798376494","https://openalex.org/W2886478610","https://openalex.org/W2891837480","https://openalex.org/W2898848825","https://openalex.org/W2906077204","https://openalex.org/W2915586987","https://openalex.org/W2919054368","https://openalex.org/W2919115771","https://openalex.org/W2945520991","https://openalex.org/W2959724594","https://openalex.org/W2980472264","https://openalex.org/W2994908203","https://openalex.org/W3007792515","https://openalex.org/W3020138377","https://openalex.org/W3043820883","https://openalex.org/W3102431071"],"related_works":["https://openalex.org/W3113091479","https://openalex.org/W2162899405","https://openalex.org/W941090075","https://openalex.org/W2044987316","https://openalex.org/W3134374554","https://openalex.org/W2237480245","https://openalex.org/W3003272824","https://openalex.org/W2481566011","https://openalex.org/W2239213377","https://openalex.org/W2384922233"],"abstract_inverted_index":{"Modern":[0],"industrial":[1,218],"plants":[2],"generally":[3],"consist":[4],"of":[5,24,33,77,96,143,209,236],"multiple":[6],"manufacturing":[7],"units,":[8],"and":[9,27,79,99,122,176,189,238],"the":[10,22,30,34,38,55,71,89,125,137,140,144,153,163,168,186,199,210,225],"local":[11,39,104],"correlation":[12,26,95],"within":[13,106],"each":[14,87,115],"unit":[15,109],"can":[16,110,148,170,194,228],"be":[17,49,111,149,195],"used":[18],"to":[19,69,86,129,162,197,202],"effectively":[20,229],"alleviate":[21],"effect":[23],"spurious":[25],"meticulously":[28],"reflect":[29],"operation":[31,85,108,141],"status":[32,142],"process":[35,97,231],"system.":[36],"Therefore,":[37],"correlation,":[40],"which":[41],"is":[42,67,120,213],"called":[43],"spatial":[44,80,100,239],"information":[45,91,101,179],"here,":[46],"should":[47],"also":[48,171],"taken":[50],"into":[51],"consideration":[52],"when":[53],"developing":[54],"monitoring":[56,63,72,133,205],"model.":[57,134],"In":[58],"this":[59],"study,":[60],"a":[61,118,131],"cascaded":[62],"network":[64,166,201],"(MoniNet)":[65],"method":[66,212,227],"proposed":[68,200,211,226],"develop":[70],"model":[73],"with":[74,156],"concurrent":[75,234],"analytics":[76,235],"temporal":[78,90,237],"information.":[81,240],"By":[82],"implementing":[83],"convolutional":[84,116,164,183],"variable,":[88],"that":[92,102,224],"reveals":[93],"dynamic":[94],"data":[98],"reflects":[103],"characteristics":[105],"individual":[107],"extracted":[112],"simultaneously.":[113],"For":[114],"feature,":[117],"submodel":[119,190],"developed":[121,138],"then":[123],"all":[124],"submodels":[126],"are":[127],"integrated":[128],"generate":[130],"final":[132],"Based":[135],"on":[136],"model,":[139],"newly":[145],"collected":[146],"sample":[147],"identified":[150],"by":[151,180,233],"comparing":[152],"calculated":[154],"statistics":[155],"their":[157],"corresponding":[158],"control":[159],"limits.":[160],"Similar":[161],"neural":[165],"(CNN),":[167],"MoniNet":[169,193],"expand":[172],"its":[173],"receptive":[174],"field":[175],"capture":[177],"deeper":[178],"adding":[181],"more":[182],"layers.":[184],"Besides,":[185],"filter":[187],"selection":[188],"development":[191],"in":[192],"replaced":[196],"generalize":[198],"many":[203],"existing":[204],"strategies.":[206],"The":[207,220],"performance":[208],"validated":[214],"using":[215],"two":[216],"real":[217],"processes.":[219],"illustration":[221],"results":[222],"show":[223],"detect":[230],"anomalies":[232]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":37},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":11}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}