{"id":"https://openalex.org/W2999299646","doi":"https://doi.org/10.1109/access.2020.2965623","title":"Fault Detection in Multimode Processes Through Improved Nonlinear External Analysis Regression","display_name":"Fault Detection in Multimode Processes Through Improved Nonlinear External Analysis Regression","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2999299646","doi":"https://doi.org/10.1109/access.2020.2965623","mag":"2999299646"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2965623","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2965623","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08955894.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08955894.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101586571","display_name":"Rongrong Sun","orcid":"https://orcid.org/0000-0002-2543-7028"},"institutions":[{"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"],"is_corresponding":true,"raw_author_name":"Rongrong Sun","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Liaoning, China"],"raw_orcid":"https://orcid.org/0000-0002-2543-7028","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101586571"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2976,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.53118419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"8","issue":null,"first_page":"11208","last_page":"11218"},"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9937000274658203,"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"}},{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.9923999905586243,"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/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.7647823095321655},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.678320050239563},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5339767932891846},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5153100490570068},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4192594289779663},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3803032636642456},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27197057008743286},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24803635478019714},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23975467681884766},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23119884729385376}],"concepts":[{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.7647823095321655},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.678320050239563},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5339767932891846},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5153100490570068},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4192594289779663},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3803032636642456},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27197057008743286},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24803635478019714},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23975467681884766},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23119884729385376},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"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":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2965623","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2965623","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08955894.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:95ed44236b67425dafeca62cc301dd66","is_oa":true,"landing_page_url":"https://doaj.org/article/95ed44236b67425dafeca62cc301dd66","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":"IEEE Access, Vol 8, Pp 11208-11218 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2965623","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2965623","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08955894.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8830865568","display_name":null,"funder_award_id":"61733003","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":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2999299646.pdf","grobid_xml":"https://content.openalex.org/works/W2999299646.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W1968463597","https://openalex.org/W1974717100","https://openalex.org/W1976972876","https://openalex.org/W1983303405","https://openalex.org/W1986441054","https://openalex.org/W2001993543","https://openalex.org/W2008616192","https://openalex.org/W2016003630","https://openalex.org/W2036887017","https://openalex.org/W2050780110","https://openalex.org/W2052828853","https://openalex.org/W2060776628","https://openalex.org/W2065096592","https://openalex.org/W2072405524","https://openalex.org/W2072817519","https://openalex.org/W2076133707","https://openalex.org/W2077169609","https://openalex.org/W2079013017","https://openalex.org/W2082784639","https://openalex.org/W2083856839","https://openalex.org/W2087883561","https://openalex.org/W2092698831","https://openalex.org/W2094298886","https://openalex.org/W2103711750","https://openalex.org/W2110227608","https://openalex.org/W2123603135","https://openalex.org/W2128921897","https://openalex.org/W2137015384","https://openalex.org/W2158225746","https://openalex.org/W2158956608","https://openalex.org/W2170447682","https://openalex.org/W2287199644","https://openalex.org/W2313779128","https://openalex.org/W2318720141","https://openalex.org/W2321802415","https://openalex.org/W2333075330","https://openalex.org/W2337983776","https://openalex.org/W2357836544","https://openalex.org/W2522640709","https://openalex.org/W2588306484","https://openalex.org/W2608089442","https://openalex.org/W2766926079","https://openalex.org/W2788805965","https://openalex.org/W2890457970","https://openalex.org/W2920714358","https://openalex.org/W2936436999","https://openalex.org/W2947969165","https://openalex.org/W2955817569","https://openalex.org/W2956233373","https://openalex.org/W2956566815","https://openalex.org/W2967545389","https://openalex.org/W2971407654"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W1969346022","https://openalex.org/W2034959125","https://openalex.org/W2355687852"],"abstract_inverted_index":{"External":[0,48],"analysis":[1,16,46],"serve":[2],"as":[3],"a":[4,35,75,123,190],"cogent":[5],"approach":[6,17,38,104],"for":[7,39,95,194],"multimode":[8,40],"process":[9,174,193],"detection":[10,37,167],"in":[11,63,81,122,140],"recent":[12],"years.":[13],"However,":[14],"external":[15,45,52,111],"may":[18],"not":[19,133],"detect":[20,173],"faults":[21],"well":[22],"because":[23],"of":[24,28,127,137,156,183],"the":[25,64,69,82,102,106,150,179,184],"imprecise":[26],"extraction":[27,136],"relations":[29],"between":[30,51],"variables.":[31,144],"This":[32],"paper":[33],"proposes":[34],"fault":[36,96,195],"processes,":[41],"called":[42],"improved":[43],"nonlinear":[44],"regression.":[47],"regression":[49,93,112,147],"models":[50],"variables":[53,56,86],"and":[54,84,142,159,165,181],"main/quality":[55,65],"are":[57,169],"established":[58],"to":[59,89,118,152,171,189],"remove":[60],"mode-change-related":[61,138],"information":[62,80,139,158],"variables,":[66],"ensuring":[67],"that":[68],"following":[70,107],"work":[71],"is":[72,87,187],"performed":[73],"under":[74],"single":[76],"mode.":[77],"The":[78],"remaining":[79],"main":[83,141],"quality":[85,143],"employed":[88],"develop":[90],"an":[91],"internal":[92],"model":[94,130,148],"detection.":[97,196],"Compared":[98],"with":[99],"existing":[100],"approaches,":[101],"proposed":[103],"has":[105,149],"advantages:":[108],"(1)":[109],"In":[110],"models,":[113],"applying":[114],"kernel":[115],"orthogonal":[116],"projections":[117],"latent":[119],"structures":[120],"resulted":[121],"relatively":[124],"smaller":[125],"number":[126],"loadings,":[128],"reduced":[129],"complexity":[131],"and,":[132],"least,":[134],"efficient":[135],"(2)":[145],"Internal":[146],"capacity":[151],"improve":[153],"separation":[154],"performance":[155],"output-related":[157],"output-unrelated":[160],"information.":[161],"(3)":[162],"Two":[163],"comprehensive":[164],"perspicuous":[166],"statistics":[168],"designed":[170],"accurately":[172],"faults.":[175],"To":[176],"experimentally":[177],"verify":[178],"stability":[180],"superiority":[182],"method,":[185],"it":[186],"applied":[188],"penicillin":[191],"fermentation":[192]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
