{"id":"https://openalex.org/W3120377913","doi":"https://doi.org/10.1109/icarcv50220.2020.9305438","title":"Fault detection for Nonstationary Process with Decomposition and Analytics of Gaussian and Non-Gaussian Subspaces","display_name":"Fault detection for Nonstationary Process with Decomposition and Analytics of Gaussian and Non-Gaussian Subspaces","publication_year":2020,"publication_date":"2020-12-13","ids":{"openalex":"https://openalex.org/W3120377913","doi":"https://doi.org/10.1109/icarcv50220.2020.9305438","mag":"3120377913"},"language":"en","primary_location":{"id":"doi:10.1109/icarcv50220.2020.9305438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv50220.2020.9305438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV)","raw_type":"proceedings-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/A5077280762","display_name":"Yi Zhao","orcid":"https://orcid.org/0000-0001-5368-3595"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Zhao","raw_affiliation_strings":["College of Control Science and Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"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/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhui Zhao","raw_affiliation_strings":["College of Control Science and Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103575615","display_name":"Youxian Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youxian Sun","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077280762"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1972844,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"115","issue":null,"first_page":"642","last_page":"647"},"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":0.9976000189781189,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9825999736785889,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.7464818954467773},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.7198961973190308},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.619502067565918},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5717114806175232},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.5215587615966797},{"id":"https://openalex.org/keywords/gaussian-random-field","display_name":"Gaussian random field","score":0.5158342719078064},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.4993772506713867},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.4403529167175293},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4065241813659668},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29557332396507263},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2721955180168152},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22760260105133057},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07538560032844543}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.7464818954467773},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.7198961973190308},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.619502067565918},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5717114806175232},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.5215587615966797},{"id":"https://openalex.org/C51267290","wikidata":"https://www.wikidata.org/wiki/Q5527848","display_name":"Gaussian random field","level":4,"score":0.5158342719078064},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.4993772506713867},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.4403529167175293},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4065241813659668},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29557332396507263},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2721955180168152},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22760260105133057},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07538560032844543},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarcv50220.2020.9305438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv50220.2020.9305438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W562231173","https://openalex.org/W1965555277","https://openalex.org/W1991410152","https://openalex.org/W2015436473","https://openalex.org/W2031329197","https://openalex.org/W2043261186","https://openalex.org/W2051385221","https://openalex.org/W2051940462","https://openalex.org/W2056871913","https://openalex.org/W2064110888","https://openalex.org/W2071128523","https://openalex.org/W2094687520","https://openalex.org/W2123649031","https://openalex.org/W2143822727","https://openalex.org/W2153464267","https://openalex.org/W2441266639","https://openalex.org/W2514000312","https://openalex.org/W2772343646","https://openalex.org/W2883667036","https://openalex.org/W2886478610","https://openalex.org/W2898848825","https://openalex.org/W2939985247","https://openalex.org/W3047463300","https://openalex.org/W3104298728","https://openalex.org/W6615864648"],"related_works":["https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W3134152097","https://openalex.org/W4311388919","https://openalex.org/W2966696655","https://openalex.org/W4312290701"],"abstract_inverted_index":{"Process":[0],"monitoring":[1,194,213],"is":[2,40,83,107,143,170,177],"a":[3,65,69,100,111,136,174,226],"challenging":[4],"task":[5],"for":[6,118,179],"modern":[7],"industrial":[8],"processes":[9],"which":[10,32,59,154,169],"are":[11,196,223],"commonly":[12],"nonstationary":[13,119,126],"in":[14,46,55,95],"nature,":[15],"revealing":[16,180],"typical":[17,54],"non-Gaussian":[18,50,93,103,149,203],"characteristics.":[19],"Nowadays,":[20],"data-driven":[21],"based":[22,140],"fault":[23,79],"detection":[24],"methods":[25],"have":[26],"drawn":[27],"increasing":[28],"attention,":[29],"most":[30],"of":[31,113,219],"work":[33],"under":[34],"an":[35],"assumption":[36],"that":[37],"the":[38,48,56,89,123,166,188,200,220],"process":[39,120,127],"subject":[41],"to":[42,78,85,132,145,198],"Gaussian":[43,91,101,147,167,201],"distribution.":[44],"But":[45],"practice,":[47],"underlying":[49,90],"characteristics":[51],"may":[52,75],"be":[53,61,76,129],"complex":[57],"process,":[58],"cannot":[60],"properly":[62],"enclosed":[63],"by":[64,109,173],"statistical":[66,175],"model":[67],"with":[68],"close":[70],"confidence":[71],"region":[72],"and":[73,87,92,102,148,184,202,211,217],"thus":[74,206],"insensitive":[77],"detection.":[80],"Hence,":[81],"it":[82],"necessary":[84],"explore":[86,199],"separate":[88,146],"distributions":[94],"fine-grain.":[96],"In":[97],"this":[98],"work,":[99],"subspace":[104,115],"decomposition":[105],"method":[106,222],"proposed":[108,221],"designing":[110],"variant":[112],"stationary":[114],"analysis":[116],"(VSSA)":[117],"monitoring.":[121],"First,":[122],"whole":[124],"time-wise":[125],"can":[128],"neatly":[130],"converted":[131],"condition-wise":[133],"slices.":[134],"Then,":[135],"Monte":[137],"Carlo":[138],"sampling":[139],"VSSA":[141],"technique":[142],"designed":[144],"subspaces":[150],"from":[151],"each":[152],"other,":[153],"focuses":[155],"on":[156,225],"analyzing":[157],"sample":[158],"distribution":[159,204,209],"rather":[160],"than":[161],"time":[162],"series":[163],"properties.":[164],"Here":[165],"subspace,":[168],"readily":[171],"characterized":[172],"model,":[176],"used":[178],"similar":[181],"condition":[182,190],"slices":[183],"affiliate":[185],"them":[186],"into":[187],"same":[189],"mode.":[191],"And":[192],"two":[193],"statistics":[195],"developed":[197],"structures,":[205],"providing":[207],"fine-grained":[208],"analytics":[210],"promoting":[212],"performance.":[214],"The":[215],"feasibility":[216],"performance":[218],"demonstrated":[224],"real":[227],"thermal":[228],"power":[229],"plant":[230],"process.":[231]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
