{"id":"https://openalex.org/W3046225020","doi":"https://doi.org/10.23919/ecc51009.2020.9143832","title":"Fault diagnosis using PCA-Bayesian Network classifier with unknown faults","display_name":"Fault diagnosis using PCA-Bayesian Network classifier with unknown faults","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3046225020","doi":"https://doi.org/10.23919/ecc51009.2020.9143832","mag":"3046225020"},"language":"en","primary_location":{"id":"doi:10.23919/ecc51009.2020.9143832","is_oa":false,"landing_page_url":"https://doi.org/10.23919/ecc51009.2020.9143832","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 European Control Conference (ECC)","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/A5108584112","display_name":"M. Amine Atoui","orcid":"https://orcid.org/0000-0003-1893-5819"},"institutions":[{"id":"https://openalex.org/I2802204017","display_name":"Universit\u00e9 de Bretagne Sud","ror":"https://ror.org/04ed7fw48","country_code":"FR","type":"education","lineage":["https://openalex.org/I2802204017"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"M. Amine Atoui","raw_affiliation_strings":["Lab-STICC, CNRS, UBS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lab-STICC, CNRS, UBS","institution_ids":["https://openalex.org/I2802204017"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086269058","display_name":"Achraf Cohen","orcid":"https://orcid.org/0000-0002-7843-4517"},"institutions":[{"id":"https://openalex.org/I83683471","display_name":"University of West Florida","ror":"https://ror.org/002w4zy91","country_code":"US","type":"education","lineage":["https://openalex.org/I83683471"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Cohen","raw_affiliation_strings":["Mathematics and Statistics Department, University of West Florida, Pensacola, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mathematics and Statistics Department, University of West Florida, Pensacola, FL, USA","institution_ids":["https://openalex.org/I83683471"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8936,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.74063276,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2039","last_page":"2044"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":1.0,"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":1.0,"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":0.9879999756813049,"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/T14470","display_name":"Advanced Data Processing Techniques","score":0.98580002784729,"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":0.7060693502426147},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6752819418907166},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.66208416223526},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5761619210243225},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5549913048744202},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5341889262199402},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5324367880821228},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5231757760047913},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5066526532173157},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4657272696495056},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.43002182245254517},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.42930343747138977},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.422812283039093},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4103260934352875},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.08326590061187744}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7060693502426147},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6752819418907166},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.66208416223526},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5761619210243225},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5549913048744202},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5341889262199402},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5324367880821228},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5231757760047913},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5066526532173157},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4657272696495056},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.43002182245254517},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.42930343747138977},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.422812283039093},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4103260934352875},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.08326590061187744},{"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},{"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/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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.23919/ecc51009.2020.9143832","is_oa":false,"landing_page_url":"https://doi.org/10.23919/ecc51009.2020.9143832","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 European Control Conference (ECC)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-03175820v1","is_oa":false,"landing_page_url":"https://inria.hal.science/hal-03175820","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ECC 2020, 2020, Online, Russia","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1149231055","https://openalex.org/W1506534120","https://openalex.org/W1521944817","https://openalex.org/W1855550284","https://openalex.org/W1969158915","https://openalex.org/W1970529538","https://openalex.org/W1979357005","https://openalex.org/W1989087337","https://openalex.org/W1989241020","https://openalex.org/W1990384678","https://openalex.org/W1999935041","https://openalex.org/W2000858991","https://openalex.org/W2004186751","https://openalex.org/W2038180527","https://openalex.org/W2084408974","https://openalex.org/W2093049199","https://openalex.org/W2147129131","https://openalex.org/W2158958729","https://openalex.org/W2312120796","https://openalex.org/W2480738848","https://openalex.org/W2487355935","https://openalex.org/W2496323672","https://openalex.org/W2541638007","https://openalex.org/W2967723820","https://openalex.org/W4249625715","https://openalex.org/W6721793220","https://openalex.org/W6776535907"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W2126145365","https://openalex.org/W2036609560","https://openalex.org/W346861917","https://openalex.org/W3024018414","https://openalex.org/W1542592062","https://openalex.org/W2474947501"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"propose":[4],"an":[5],"original":[6],"framework":[7],"for":[8,27],"fault":[9,28],"diagnosis":[10],"with":[11],"Bayesian":[12],"networks.":[13],"The":[14,30],"proposed":[15,31,60],"approach":[16],"uses":[17],"conditional":[18],"Gaussian":[19],"network":[20],"to":[21,35,63],"improve":[22],"principal":[23],"component":[24],"analysis":[25],"scheme":[26],"diagnosis.":[29],"method":[32,61],"allows":[33],"us":[34],"consider":[36],"known":[37],"and":[38,53],"unknown":[39],"class":[40],"of":[41,58],"faults.":[42],"Performance":[43],"evaluation":[44],"using":[45],"the":[46,59],"Tennessee":[47],"Eastman":[48],"Process":[49],"data":[50],"is":[51],"presented":[52],"shows":[54],"a":[55],"superior":[56],"performance":[57],"compared":[62],"existing":[64],"methods.":[65]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
