{"id":"https://openalex.org/W4206552269","doi":"https://doi.org/10.1109/tim.2021.3136260","title":"A Novel Fault Detection Method Based on the Extraction of Slow Features for Dynamic Nonstationary Processes","display_name":"A Novel Fault Detection Method Based on the Extraction of Slow Features for Dynamic Nonstationary Processes","publication_year":2021,"publication_date":"2021-12-20","ids":{"openalex":"https://openalex.org/W4206552269","doi":"https://doi.org/10.1109/tim.2021.3136260"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2021.3136260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3136260","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-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/A5100459936","display_name":"Jie Dong","orcid":"https://orcid.org/0000-0001-7585-6637"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Dong","raw_affiliation_strings":["Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7585-6637","affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040127812","display_name":"Yaqi Wang","orcid":"https://orcid.org/0000-0003-3008-8317"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaqi Wang","raw_affiliation_strings":["Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3008-8317","affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016153320","display_name":"Kaixiang Peng","orcid":"https://orcid.org/0000-0001-8314-3047"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaixiang Peng","raw_affiliation_strings":["Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8314-3047","affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I92403157"],"apc_list":null,"apc_paid":null,"fwci":4.4662,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.95121691,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"11"},"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/T12282","display_name":"Mineral Processing and Grinding","score":0.996999979019165,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.919830322265625},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.6038894057273865},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5373287200927734},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.5264240503311157},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5188866257667542},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4811202585697174},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46616819500923157},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4524648189544678},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.43707743287086487},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4300120174884796},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.42954131960868835},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4008515179157257},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31383877992630005}],"concepts":[{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.919830322265625},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.6038894057273865},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5373287200927734},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.5264240503311157},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5188866257667542},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4811202585697174},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46616819500923157},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4524648189544678},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.43707743287086487},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4300120174884796},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.42954131960868835},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4008515179157257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31383877992630005},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2021.3136260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3136260","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-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":[{"id":"https://openalex.org/G2135398491","display_name":"\u9762\u5411\u7cfb\u7edf\u5c42\u7ea7\u591a\u5de5\u51b5\u4e0b\u5e26\u94a2\u70ed\u8f67\u5168\u6d41\u7a0b\u8d28\u91cf\u76d1\u6d4b\u4e0e\u6545\u969c\u8bca\u65ad\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61873024","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3131941308","display_name":null,"funder_award_id":"61903030","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4043084518","display_name":null,"funder_award_id":"2021YFB3301201","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5345354591","display_name":null,"funder_award_id":"61773053","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"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1966863755","https://openalex.org/W1977272845","https://openalex.org/W2007710878","https://openalex.org/W2021550734","https://openalex.org/W2034707435","https://openalex.org/W2068193536","https://openalex.org/W2074374590","https://openalex.org/W2075639004","https://openalex.org/W2110603299","https://openalex.org/W2111637385","https://openalex.org/W2136295067","https://openalex.org/W2146444479","https://openalex.org/W2158958729","https://openalex.org/W2275031392","https://openalex.org/W2471656365","https://openalex.org/W2602750048","https://openalex.org/W2734412439","https://openalex.org/W2772343646","https://openalex.org/W2775072185","https://openalex.org/W2792056293","https://openalex.org/W2886478610","https://openalex.org/W2898848825","https://openalex.org/W2904132078","https://openalex.org/W2905025727","https://openalex.org/W2937397447","https://openalex.org/W2945169080","https://openalex.org/W3007792515","https://openalex.org/W3048582611","https://openalex.org/W3056537781","https://openalex.org/W3089317657","https://openalex.org/W3107595400","https://openalex.org/W3108475634","https://openalex.org/W3109521448","https://openalex.org/W3134253489","https://openalex.org/W3152801264","https://openalex.org/W3196531040","https://openalex.org/W3200857472","https://openalex.org/W4230884390"],"related_works":["https://openalex.org/W4382795578","https://openalex.org/W2355463328","https://openalex.org/W2402648945","https://openalex.org/W1431147547","https://openalex.org/W2055761197","https://openalex.org/W2053213469","https://openalex.org/W2057608111","https://openalex.org/W2927068219","https://openalex.org/W3094086031","https://openalex.org/W2774527540"],"abstract_inverted_index":{"The":[0],"industrial":[1],"process":[2,175,179],"often":[3,41],"shows":[4],"nonstationary":[5,72,103],"characteristic,":[6],"such":[7],"as":[8,143],"time-varying":[9],"mean":[10],"and":[11,48,73,83,134,162,176,188],"variance,":[12],"due":[13],"to":[14,64,115,129,157,183],"the":[15,27,37,66,98,105,124,144,150,160,185,189,193],"unmeasured":[16],"disturbances,":[17],"adjustments":[18],"of":[19,26,29,39,68,152,192],"production":[20],"plans,":[21],"operator":[22],"interventions,":[23],"etc.":[24],"Because":[25],"overlook":[28],"nonstationarity,":[30],"traditional":[31],"multivariate":[32],"statistical":[33],"methods":[34],"based":[35,87,137],"on":[36,88,138],"assumption":[38],"stationarity":[40],"cause":[42],"low":[43],"fault":[44,59,69],"detection":[45,60,70],"rate":[46,52],"(FDR)":[47],"high":[49],"false":[50],"alarm":[51],"(FAR).":[53],"In":[54],"this":[55],"article,":[56],"a":[57,117],"novel":[58],"framework":[61,187],"is":[62,141,155],"proposed":[63,186],"improve":[65],"performance":[67],"when":[71],"stationary":[74,106],"variables":[75,94],"coexist.":[76],"It":[77],"combines":[78],"slow":[79,121],"feature":[80,131],"analysis":[81,113],"(SFA)":[82],"K-nearest":[84],"neighbor":[85],"(KNN)":[86],"Mahalanobis":[89,139],"distance":[90,136],"(SFA-MDKNN).":[91],"First,":[92],"stationary/nonstationary":[93],"are":[95,108,127,164,181],"distinguished":[96],"by":[97,110,168],"unit":[99],"root":[100],"test.":[101],"For":[102],"variables,":[104],"residuals":[107],"obtained":[109],"Johansen":[111],"cointegration":[112],"(CA)":[114],"form":[116],"combination":[118,125],"matrix.":[119],"Second,":[120],"features":[122],"in":[123],"matrix":[126],"extracted":[128],"achieve":[130],"level":[132],"fusion,":[133],"KNN":[135,153],"one":[140],"introduced":[142],"monitoring":[145],"index.":[146],"Finally,":[147],"considering":[148],"that":[149],"effect":[151],"algorithm":[154],"susceptible":[156],"data":[158],"distribution,":[159],"FDR":[161],"FAR":[163],"taken":[165],"into":[166],"account":[167],"setting":[169],"dynamic":[170],"control":[171],"limits.":[172],"Tennessee":[173],"Eastman":[174],"hot":[177],"rolling":[178],"(HRP)":[180],"used":[182],"validate":[184],"computational":[190],"efficiency":[191],"algorithm.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}