{"id":"https://openalex.org/W2955033741","doi":"https://doi.org/10.1109/tnnls.2019.2920903","title":"Fault Diagnosis of Complex Processes Using Sparse Kernel Local Fisher Discriminant Analysis","display_name":"Fault Diagnosis of Complex Processes Using Sparse Kernel Local Fisher Discriminant Analysis","publication_year":2019,"publication_date":"2019-06-28","ids":{"openalex":"https://openalex.org/W2955033741","doi":"https://doi.org/10.1109/tnnls.2019.2920903","mag":"2955033741","pmid":"https://pubmed.ncbi.nlm.nih.gov/31265419"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2019.2920903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2920903","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","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/A5017721496","display_name":"Kai Zhong","orcid":"https://orcid.org/0000-0002-9993-6954"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]},{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zhong","raw_affiliation_strings":["Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-9993-6954","affiliations":[{"raw_affiliation_string":"Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992","https://openalex.org/I4210092944"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032636287","display_name":"Min Han","orcid":"https://orcid.org/0000-0002-2964-4884"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]},{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Han","raw_affiliation_strings":["Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-2964-4884","affiliations":[{"raw_affiliation_string":"Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992","https://openalex.org/I4210092944"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037428599","display_name":"Tie Qiu","orcid":"https://orcid.org/0000-0003-2324-2523"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tie Qiu","raw_affiliation_strings":["School of Computer Science and Technology, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-2324-2523","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Tianjin University, Tianjin, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091496560","display_name":"Bing Han","orcid":"https://orcid.org/0000-0002-4890-7563"},"institutions":[{"id":"https://openalex.org/I4210097049","display_name":"Shanghai Ship and Shipping Research Institute","ror":"https://ror.org/00z9npm78","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210097049"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Han","raw_affiliation_strings":["State Key Laboratory of Navigation and Safety Technology, Shanghai Ship and Shipping Research Institute, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Navigation and Safety Technology, Shanghai Ship and Shipping Research Institute, Shanghai, China","institution_ids":["https://openalex.org/I4210097049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.1913,"has_fulltext":false,"cited_by_count":86,"citation_normalized_percentile":{"value":0.97051316,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"31","issue":"5","first_page":"1581","last_page":"1591"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9894000291824341,"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":0.9799000024795532,"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/interpretability","display_name":"Interpretability","score":0.7272534370422363},{"id":"https://openalex.org/keywords/kernel-fisher-discriminant-analysis","display_name":"Kernel Fisher discriminant analysis","score":0.7176129221916199},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6349132061004639},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5900439620018005},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5828203558921814},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5718140006065369},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5671525001525879},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5402910113334656},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5390545129776001},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4460139572620392},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.4368188679218292},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.42907214164733887},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.4158990979194641},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4137597978115082},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.378385066986084},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.2727065086364746},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23049527406692505}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7272534370422363},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.7176129221916199},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6349132061004639},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5900439620018005},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5828203558921814},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5718140006065369},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5671525001525879},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5402910113334656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5390545129776001},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4460139572620392},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.4368188679218292},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.42907214164733887},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.4158990979194641},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4137597978115082},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.378385066986084},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2727065086364746},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23049527406692505},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2019.2920903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2920903","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:31265419","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31265419","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 neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5600000023841858}],"awards":[{"id":"https://openalex.org/G876797204","display_name":null,"funder_award_id":"61773087","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G961954810","display_name":null,"funder_award_id":"15QB1400800","funder_id":"https://openalex.org/F4320327803","funder_display_name":"Shanghai Rising-Star Program"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327803","display_name":"Shanghai Rising-Star Program","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W637422688","https://openalex.org/W923818475","https://openalex.org/W1506281249","https://openalex.org/W1897892887","https://openalex.org/W1915008591","https://openalex.org/W1966863755","https://openalex.org/W1983745919","https://openalex.org/W1991519797","https://openalex.org/W2004186751","https://openalex.org/W2021894918","https://openalex.org/W2027717478","https://openalex.org/W2087528435","https://openalex.org/W2088540877","https://openalex.org/W2109531142","https://openalex.org/W2109574129","https://openalex.org/W2122825543","https://openalex.org/W2126998396","https://openalex.org/W2149414429","https://openalex.org/W2161141520","https://openalex.org/W2201427885","https://openalex.org/W2344734818","https://openalex.org/W2344745309","https://openalex.org/W2441266639","https://openalex.org/W2442309921","https://openalex.org/W2563202971","https://openalex.org/W2567394033","https://openalex.org/W2580937131","https://openalex.org/W2588880771","https://openalex.org/W2588932259","https://openalex.org/W2739031780","https://openalex.org/W2741385306","https://openalex.org/W2754813553","https://openalex.org/W2771499866","https://openalex.org/W2775523681","https://openalex.org/W2806149340","https://openalex.org/W3014771378","https://openalex.org/W4205687621","https://openalex.org/W6676189307"],"related_works":["https://openalex.org/W2141981133","https://openalex.org/W2386228546","https://openalex.org/W2086055175","https://openalex.org/W2365801610","https://openalex.org/W2388048830","https://openalex.org/W2150796457","https://openalex.org/W2016459271","https://openalex.org/W2114217318","https://openalex.org/W2395040056","https://openalex.org/W2129407254"],"abstract_inverted_index":{"As":[0],"an":[1,79],"outstanding":[2],"discriminant":[3,7],"analysis":[4,8],"technique,":[5],"Fisher":[6],"(FDA)":[9],"gained":[10],"extensive":[11],"attention":[12],"in":[13,35],"supervised":[14],"dimensionality":[15],"reduction":[16],"and":[17,63,113,141,150,192,208],"fault":[18,60,147],"diagnosis":[19,148,203],"fields.":[20],"However,":[21],"it":[22,39,86],"typically":[23],"ignores":[24],"the":[25,28,47,53,69,89,101,109,114,122,129,138,146,172,201,211],"multimodality":[26,91],"within":[27],"measured":[29],"data,":[30],"which":[31,175],"may":[32],"cause":[33],"infeasibility":[34],"practice.":[36],"In":[37,156],"addition,":[38,157],"generally":[40],"incorporates":[41],"all":[42],"process":[43,191,197],"variables":[44,104],"without":[45],"emphasizing":[46],"key":[48],"faulty":[49,103],"ones":[50],"when":[51],"modeling":[52],"complex":[54],"process,":[55],"thus":[56],"leading":[57],"to":[58,163,180],"degraded":[59],"classification":[61],"capability":[62],"poor":[64],"model":[65,151,162],"interpretability.":[66],"To":[67],"ease":[68],"above":[70],"two":[71],"drawbacks":[72],"of":[73],"conventional":[74],"FDA,":[75],"this":[76],"brief":[77],"presents":[78],"advantageously":[80],"sparse":[81,167],"local":[82,94,130,169],"FDA":[83],"(SLFDA)":[84],"model,":[85],"first":[87],"preserves":[88],"within-class":[90],"by":[92,171],"introducing":[93],"weighting":[95],"factors":[96],"into":[97],"scatter":[98],"matrix.":[99],"Then,":[100],"responsible":[102],"are":[105,134,153],"identified":[106],"automatically":[107],"through":[108,121],"elastic":[110],"net":[111],"algorithm,":[112],"current":[115],"optimization":[116],"problem":[117],"is":[118,176,205],"subsequently":[119],"settled":[120],"feasible":[123],"gradient":[124],"direction":[125],"method.":[126],"Since":[127],"then,":[128],"data":[131],"structure":[132],"characteristics":[133],"exploited":[135],"from":[136],"both":[137,198],"sample":[139],"dimension":[140,143],"variable":[142],"so":[144],"that":[145,200],"performance":[149],"interpretability":[152],"significantly":[154],"enhanced.":[155],"we":[158],"naturally":[159],"extend":[160],"SLFDA":[161],"nonlinear":[164],"variant":[165],"(i.e.,":[166],"kernel":[168,173],"FDA)":[170],"trick,":[174],"substantially":[177],"more":[178,206],"resistant":[179],"strong":[181],"nonlinearity.":[182],"The":[183],"simulation":[184],"studies":[185],"on":[186],"Tennessee":[187],"Eastman":[188],"(TE)":[189],"benchmark":[190],"real-world":[193],"diesel":[194],"engine":[195],"working":[196],"validate":[199],"novel":[202],"strategy":[204],"accurate":[207],"reliable":[209],"than":[210],"existing":[212],"state-of-the-art":[213],"methods.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}