{"id":"https://openalex.org/W1975236953","doi":"https://doi.org/10.1109/grc.2011.6122700","title":"Hybrid intelligent fault diagnosis based on quotient space","display_name":"Hybrid intelligent fault diagnosis based on quotient space","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W1975236953","doi":"https://doi.org/10.1109/grc.2011.6122700","mag":"1975236953"},"language":"en","primary_location":{"id":"doi:10.1109/grc.2011.6122700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/grc.2011.6122700","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Granular Computing","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/A5100407236","display_name":"Jinfeng Zhang","orcid":"https://orcid.org/0000-0002-8406-9261"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinfeng Zhang","raw_affiliation_strings":["State Key Laboratory for Manufacturing Systems Engineering, Xian Jiaotong University, Xi'an, China","State key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Manufacturing Systems Engineering, Xian Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"State key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027894205","display_name":"Chuang Sun","orcid":"https://orcid.org/0000-0001-6616-3791"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuang Sun","raw_affiliation_strings":["State Key Laboratory for Manufacturing Systems Engineering, Xian Jiaotong University, Xi'an, China","State key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Manufacturing Systems Engineering, Xian Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"State key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002224846","display_name":"Zhousuo Zhang","orcid":"https://orcid.org/0000-0003-1299-8974"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhousuo Zhang","raw_affiliation_strings":["State Key Laboratory for Manufacturing Systems Engineering, Xian Jiaotong University, Xi'an, China","State key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Manufacturing Systems Engineering, Xian Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"State key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103407942","display_name":"Zhengjia He","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengjia He","raw_affiliation_strings":["State Key Laboratory for Manufacturing Systems Engineering, Xian Jiaotong University, Xi'an, China","State key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Manufacturing Systems Engineering, Xian Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"State key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12919255,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"796","last_page":"801"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13955","display_name":"Evaluation Methods in Various Fields","score":0.8744999766349792,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13955","display_name":"Evaluation Methods in Various Fields","score":0.8744999766349792,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13832","display_name":"Advanced Decision-Making Techniques","score":0.8235999941825867,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14225","display_name":"Advanced Sensor and Control Systems","score":0.8101000189781189,"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":0.6163032054901123},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.6021303534507751},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5642361044883728},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5585666298866272},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5547785758972168},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5102410316467285},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.49483054876327515},{"id":"https://openalex.org/keywords/equivalence","display_name":"Equivalence (formal languages)","score":0.45268312096595764},{"id":"https://openalex.org/keywords/quotient-space","display_name":"Quotient space (topology)","score":0.4304388761520386},{"id":"https://openalex.org/keywords/hybrid-system","display_name":"Hybrid system","score":0.4253135919570923},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41855210065841675},{"id":"https://openalex.org/keywords/quotient","display_name":"Quotient","score":0.37288135290145874},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35686659812927246},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.31811457872390747},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23538392782211304}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6163032054901123},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.6021303534507751},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5642361044883728},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5585666298866272},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5547785758972168},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5102410316467285},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.49483054876327515},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.45268312096595764},{"id":"https://openalex.org/C40753290","wikidata":"https://www.wikidata.org/wiki/Q1139111","display_name":"Quotient space (topology)","level":3,"score":0.4304388761520386},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.4253135919570923},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41855210065841675},{"id":"https://openalex.org/C199422724","wikidata":"https://www.wikidata.org/wiki/Q41118","display_name":"Quotient","level":2,"score":0.37288135290145874},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35686659812927246},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31811457872390747},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23538392782211304},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/grc.2011.6122700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/grc.2011.6122700","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Granular Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1521708037","https://openalex.org/W2082805068","https://openalex.org/W2161535772","https://openalex.org/W2390804706"],"related_works":["https://openalex.org/W2042649637","https://openalex.org/W1584507652","https://openalex.org/W2948542527","https://openalex.org/W4295535217","https://openalex.org/W2018938659","https://openalex.org/W2971957670","https://openalex.org/W1967884200","https://openalex.org/W2951131903","https://openalex.org/W2484459614","https://openalex.org/W3023861739"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,14,104,128,142],"problem":[3],"that":[4,127],"existing":[5],"hybrid":[6,35,107,132],"intelligent":[7,36],"models":[8],"do":[9],"not":[10],"take":[11],"into":[12],"account":[13],"advantages":[15,27],"and":[16,22,51,59,80],"limitations":[17],"of":[18,28,34,95,106,116,131,145],"different":[19,29],"diagnostic":[20],"methods":[21],"fail":[23],"to":[24,113,135],"achieve":[25],"complementary":[26],"classifiers,":[30],"a":[31],"new":[32],"model":[33,110,133],"fault":[37,114],"diagnosis":[38,115],"based":[39],"on":[40],"quotient":[41],"space":[42],"is":[43,70,111,138],"proposed.":[44],"In":[45],"this":[46],"model,":[47],"samples":[48],"are":[49,54,83,97],"granulated":[50],"granular":[52],"layers":[53],"constructed":[55],"by":[56,72,85,99],"calculating":[57],"equivalence":[58],"cluster":[60],"analysis.":[61],"Meanwhile,":[62],"core":[63],"features":[64,73],"set":[65],"(CFS)":[66],"in":[67,89,119],"every":[68],"layer":[69],"extracted":[71],"reduction":[74],"algorithm.":[75],"Then,":[76],"support":[77],"vector":[78],"machine":[79],"anfis":[81],"classifier":[82],"trained":[84],"CFS":[86],"as":[87,103],"sub-classifiers":[88,96],"corresponding":[90],"layer.":[91],"Finally,":[92],"all":[93,146],"results":[94,125],"integrated":[98],"weighted":[100],"voting":[101],"method":[102],"output":[105],"model.":[108],"This":[109],"applied":[112],"roller":[117],"bearing":[118,120],"test":[121],"bench.":[122],"The":[123],"application":[124],"show":[126],"classification":[129],"accuracy":[130,144],"reaches":[134],"100%,":[136],"which":[137],"2.2%":[139],"higher":[140],"than":[141],"highest":[143],"sub-classifiers.":[147]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
