{"id":"https://openalex.org/W1974533575","doi":"https://doi.org/10.1109/tie.2012.2218559","title":"Rotor Faults Diagnosis Using Feature Selection and Nearest Neighbors Rule: Application to a Turbogenerator","display_name":"Rotor Faults Diagnosis Using Feature Selection and Nearest Neighbors Rule: Application to a Turbogenerator","publication_year":2012,"publication_date":"2012-09-12","ids":{"openalex":"https://openalex.org/W1974533575","doi":"https://doi.org/10.1109/tie.2012.2218559","mag":"1974533575"},"language":"en","primary_location":{"id":"doi:10.1109/tie.2012.2218559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2012.2218559","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Industrial Electronics","raw_type":"journal-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/A5054062267","display_name":"Melisande Biet","orcid":null},"institutions":[{"id":"https://openalex.org/I4210143116","display_name":"\u00c9lectricit\u00e9 de France (France)","ror":"https://ror.org/03wb8xz10","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210143116"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Melisande Biet","raw_affiliation_strings":["Research and Development Division, Electricit\u00e9 de France, Clamart, France","Research and Development Division, Electricit\u00e9 de France (EDF) , Clamart Cedex, France"],"affiliations":[{"raw_affiliation_string":"Research and Development Division, Electricit\u00e9 de France, Clamart, France","institution_ids":["https://openalex.org/I4210143116"]},{"raw_affiliation_string":"Research and Development Division, Electricit\u00e9 de France (EDF) , Clamart Cedex, France","institution_ids":["https://openalex.org/I4210143116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5054062267"],"corresponding_institution_ids":["https://openalex.org/I4210143116"],"apc_list":null,"apc_paid":null,"fwci":10.7898,"has_fulltext":false,"cited_by_count":75,"citation_normalized_percentile":{"value":0.98154168,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"60","issue":"9","first_page":"4063","last_page":"4073"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9991000294685364,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9991000294685364,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9984999895095825,"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/T13891","display_name":"Engineering Diagnostics and Reliability","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/rotor","display_name":"Rotor (electric)","score":0.6363076567649841},{"id":"https://openalex.org/keywords/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.5673083662986755},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5372723340988159},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.46308332681655884},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.45097583532333374},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.444513201713562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4367114305496216},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38176798820495605},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33386266231536865},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32564955949783325},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.08671888709068298}],"concepts":[{"id":"https://openalex.org/C17281054","wikidata":"https://www.wikidata.org/wiki/Q193466","display_name":"Rotor (electric)","level":2,"score":0.6363076567649841},{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.5673083662986755},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5372723340988159},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.46308332681655884},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.45097583532333374},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.444513201713562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4367114305496216},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38176798820495605},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33386266231536865},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32564955949783325},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.08671888709068298},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tie.2012.2218559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2012.2218559","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Industrial Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1966278166","https://openalex.org/W1986981439","https://openalex.org/W1998264828","https://openalex.org/W2005821667","https://openalex.org/W2010554546","https://openalex.org/W2013346461","https://openalex.org/W2020296181","https://openalex.org/W2026535637","https://openalex.org/W2028506029","https://openalex.org/W2053712902","https://openalex.org/W2054953158","https://openalex.org/W2078492899","https://openalex.org/W2094647223","https://openalex.org/W2100831652","https://openalex.org/W2103155805","https://openalex.org/W2103616250","https://openalex.org/W2104468024","https://openalex.org/W2121254824","https://openalex.org/W2127136782","https://openalex.org/W2127480543","https://openalex.org/W2128916170","https://openalex.org/W2129177092","https://openalex.org/W2134177842","https://openalex.org/W2139783633","https://openalex.org/W2140336071","https://openalex.org/W2148633389","https://openalex.org/W2151168325","https://openalex.org/W2156027618","https://openalex.org/W2157947466","https://openalex.org/W2165337740","https://openalex.org/W2183195208","https://openalex.org/W2592149413","https://openalex.org/W6663864751","https://openalex.org/W6663948313","https://openalex.org/W6674523029","https://openalex.org/W6675523483","https://openalex.org/W6675669426","https://openalex.org/W6683635933","https://openalex.org/W6685959973"],"related_works":["https://openalex.org/W2811390910","https://openalex.org/W2146076056","https://openalex.org/W2144059113","https://openalex.org/W1991269640","https://openalex.org/W3003836766","https://openalex.org/W1964120219","https://openalex.org/W4246585671","https://openalex.org/W2000165426","https://openalex.org/W2385132419","https://openalex.org/W2345184372"],"abstract_inverted_index":{"Among":[0],"failures":[1],"that":[2,74],"are":[3],"observed":[4],"in":[5,21,101],"power":[6],"plants,":[7],"rotor":[8,27,31,43,113],"faults":[9,28,114],"have":[10,18,122],"often":[11],"been":[12,19,81,123],"recorded.":[13],"Thus,":[14],"radial":[15],"flux":[16,44,67],"probes":[17],"introduced":[20],"most":[22],"generators":[23],"to":[24,56,83,140],"anticipate":[25],"heavy":[26],"such":[29],"as":[30],"ground":[32],"faults.":[33,196],"However,":[34],"the":[35,47,85,150,154,160,166,178,185],"commonly":[36,186],"used":[37,187],"signal":[38,188],"processing":[39,189],"done":[40],"with":[41,170],"those":[42],"measurements":[45],"makes":[46],"diagnosis":[48,59,182],"complicated.":[49],"The":[50],"aim":[51],"of":[52,94,134,184,195],"this":[53,108],"paper":[54],"is":[55,90,137,147,163],"present":[57],"a":[58,76,91,95,103,132,144,176],"method":[60],"based":[61],"on":[62],"statistical":[63],"pattern":[64],"recognition":[65],"using":[66,165],"probe":[68],"and":[69,111,153,172],"classical":[70],"electric":[71],"measurements.":[72],"For":[73],"aim,":[75],"specific":[77],"experimental":[78,88],"setup":[79,89],"has":[80],"designed":[82],"perform":[84],"methodology.":[86],"This":[87],"small-scale":[92],"prototype":[93],"nuclear":[96],"plant":[97],"generator,":[98,109],"which":[99],"is,":[100],"fact,":[102],"direct-current-excited":[104],"synchronous":[105],"machine.":[106],"In":[107],"electrical":[110],"mechanical":[112],"can":[115],"be":[116],"carried":[117],"out.":[118],"Sixteen":[119],"functional":[120],"states":[121],"performed":[124,164],"for":[125],"five":[126],"operating":[127],"points.":[128],"From":[129],"each":[130],"measurement,":[131],"list":[133],"scalar":[135],"parameters":[136],"extracted.":[138],"Then,":[139],"reduce":[141],"their":[142],"number,":[143],"selection":[145,157],"stage":[146,162],"achieved":[148],"through":[149],"Fisher":[151],"criterion":[152],"sequential":[155],"backward":[156],"algorithm.":[158],"Finally,":[159],"classification":[161],"k-nearest":[167],"neighbors":[168],"rule":[169],"Euclidian":[171],"Mahalanobis":[173],"distances.":[174],"As":[175],"result,":[177],"methodology":[179],"developed":[180],"removes":[181],"ambiguities":[183],"by":[190],"clearly":[191],"splitting":[192],"different":[193],"types":[194]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":7}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}