{"id":"https://openalex.org/W2987349413","doi":"https://doi.org/10.1109/icca.2019.8899944","title":"An Improved PCA-based Fault Detection Method for non-Gaussian Systems Using SIP Criterion","display_name":"An Improved PCA-based Fault Detection Method for non-Gaussian Systems Using SIP Criterion","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2987349413","doi":"https://doi.org/10.1109/icca.2019.8899944","mag":"2987349413"},"language":"en","primary_location":{"id":"doi:10.1109/icca.2019.8899944","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icca.2019.8899944","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 15th International Conference on Control and Automation (ICCA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5108248637","display_name":"Mi F. Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mi F. Ren","raw_affiliation_strings":["Taiyuan University of Technology, Taiyuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taiyuan University of Technology, Taiyuan, China","institution_ids":["https://openalex.org/I9086337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101721116","display_name":"Yan Liang","orcid":"https://orcid.org/0000-0003-4596-587X"},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Liang","raw_affiliation_strings":["Taiyuan University of Technology, Taiyuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taiyuan University of Technology, Taiyuan, China","institution_ids":["https://openalex.org/I9086337"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103875813","display_name":"Ming Y. Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Y. Gong","raw_affiliation_strings":["Taiyuan University of Technology, Taiyuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taiyuan University of Technology, Taiyuan, China","institution_ids":["https://openalex.org/I9086337"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9086337"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"905","last_page":"910"},"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9836000204086304,"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/T14470","display_name":"Advanced Data Processing Techniques","score":0.982200026512146,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6410399675369263},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.5853444337844849},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5485495328903198},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4764288365840912},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4555138945579529},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3957112431526184},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06445690989494324}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6410399675369263},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.5853444337844849},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5485495328903198},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4764288365840912},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4555138945579529},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3957112431526184},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06445690989494324},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icca.2019.8899944","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icca.2019.8899944","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 15th International Conference on Control and Automation (ICCA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W35265221","https://openalex.org/W83066537","https://openalex.org/W1534416612","https://openalex.org/W1980409536","https://openalex.org/W1981554428","https://openalex.org/W1990283595","https://openalex.org/W2009253909","https://openalex.org/W2066551872","https://openalex.org/W2072405524","https://openalex.org/W2101117936","https://openalex.org/W2110810023","https://openalex.org/W2112440119","https://openalex.org/W2113713615","https://openalex.org/W2125568459","https://openalex.org/W2200355885","https://openalex.org/W2294798173","https://openalex.org/W2399703712","https://openalex.org/W2461625061","https://openalex.org/W2594878042","https://openalex.org/W2612469076","https://openalex.org/W4233228607","https://openalex.org/W4299025535","https://openalex.org/W6675479683","https://openalex.org/W6676338976","https://openalex.org/W6781870204"],"related_works":["https://openalex.org/W86946229","https://openalex.org/W3009843762","https://openalex.org/W2054360660","https://openalex.org/W1998491546","https://openalex.org/W2913439950","https://openalex.org/W3097589262","https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W1964286703","https://openalex.org/W2169866437"],"abstract_inverted_index":{"In":[0,41],"the":[1,31,34,46,50,61,70,74,91,95,103,113,120,128,150,159],"past,":[2],"many":[3],"statistical":[4],"process":[5,36,75,140],"monitoring":[6,146],"methods":[7,26],"based":[8,105,162],"on":[9],"principal":[10],"component":[11],"analysis":[12],"(PCA)":[13],"have":[14],"been":[15],"drawn":[16],"up":[17],"and":[18,100,156],"applied":[19,132],"to":[20,68,89,118,133],"various":[21],"chemical":[22],"processes.":[23],"However,":[24],"these":[25],"were":[27],"almost":[28],"proposed":[29,85,129,151],"under":[30],"assumption":[32],"that":[33,149],"monitored":[35],"data":[37],"obeys":[38],"gaussian":[39],"distribution.":[40],"this":[42],"paper,":[43],"aiming":[44],"at":[45],"non-gaussian":[47],"characteristics":[48],"of":[49,73,97,123],"system,":[51],"an":[52,78],"improved":[53,79],"PCA-based":[54],"fault":[55,106,124,163],"detection":[56,107,125,164],"method":[57,117,130,152],"is":[58,66,84,109,131,153],"presented,":[59],"where":[60],"survival":[62],"information":[63],"potential":[64],"(SIP)":[65],"used":[67],"characterize":[69],"non-Gaussian":[71,142],"randomness":[72,99],"data.":[76],"Firstly,":[77],"PCA":[80,161],"method,":[81],"called":[82],"SIP-PCA":[83,104],"by":[86,111],"using":[87,112],"SIP":[88],"minimize":[90],"reconstruction":[92],"error":[93],"from":[94],"perspective":[96],"both":[98],"magnitude.":[101],"Then,":[102],"strategy":[108],"presented":[110],"kernel":[114],"density":[115],"estimation":[116],"determine":[119],"control":[121],"limit":[122],"indicators.":[126],"Finally,":[127],"a":[134],"continuous":[135],"stirred":[136],"tank":[137],"reactor":[138],"(CSTR)":[139],"with":[141],"disturbances.":[143],"The":[144],"comparative":[145],"results":[147],"illustrate":[148],"more":[154],"reliable":[155],"effective":[157],"than":[158],"traditional":[160],"methods.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
