{"id":"https://openalex.org/W2098729161","doi":"https://doi.org/10.1109/tie.2010.2098369","title":"Machine Condition Prediction Based on Adaptive Neuro\u2013Fuzzy and High-Order Particle Filtering","display_name":"Machine Condition Prediction Based on Adaptive Neuro\u2013Fuzzy and High-Order Particle Filtering","publication_year":2010,"publication_date":"2010-12-14","ids":{"openalex":"https://openalex.org/W2098729161","doi":"https://doi.org/10.1109/tie.2010.2098369","mag":"2098729161"},"language":"en","primary_location":{"id":"doi:10.1109/tie.2010.2098369","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2010.2098369","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/A5028791879","display_name":"Chaochao Chen","orcid":"https://orcid.org/0000-0003-1419-964X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chaochao Chen","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Sch. of Electr. & Comput. Eng.,, Georgia Inst. of Technol., Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Sch. of Electr. & Comput. Eng.,, Georgia Inst. of Technol., Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068564208","display_name":"Bin Zhang","orcid":"https://orcid.org/0000-0002-3338-0463"},"institutions":[{"id":"https://openalex.org/I4210166736","display_name":"Impact Technology Development (United States)","ror":"https://ror.org/05ppvf150","country_code":"US","type":"company","lineage":["https://openalex.org/I4210166736"]},{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bin Zhang","raw_affiliation_strings":["Impact Technologies LLC, Rochester, NY, USA","Impact Technol. LLC, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Impact Technologies LLC, Rochester, NY, USA","institution_ids":["https://openalex.org/I4210166736"]},{"raw_affiliation_string":"Impact Technol. LLC, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039162074","display_name":"George Vachtsevanos","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"G. Vachtsevanos","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Sch. of Electr. & Comput. Eng.,, Georgia Inst. of Technol., Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Sch. of Electr. & Comput. Eng.,, Georgia Inst. of Technol., Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035859358","display_name":"Marcos E. Orchard","orcid":"https://orcid.org/0000-0003-4778-2719"},"institutions":[{"id":"https://openalex.org/I69737025","display_name":"University of Chile","ror":"https://ror.org/047gc3g35","country_code":"CL","type":"education","lineage":["https://openalex.org/I69737025"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"M. Orchard","raw_affiliation_strings":["Department of Electrical Engineering, University of Chile, Santiago, Chile","Dept. of Electr. Eng., Univ. of Chile, Santiago, Chile"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Chile, Santiago, Chile","institution_ids":["https://openalex.org/I69737025"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Univ. of Chile, Santiago, Chile","institution_ids":["https://openalex.org/I69737025"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":34.2717,"has_fulltext":false,"cited_by_count":247,"citation_normalized_percentile":{"value":0.99756648,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"58","issue":"9","first_page":"4353","last_page":"4364"},"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":0.9976999759674072,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adaptive-neuro-fuzzy-inference-system","display_name":"Adaptive neuro fuzzy inference system","score":0.6430370807647705},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5953264236450195},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5351776480674744},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.5300934910774231},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5236303806304932},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5214288234710693},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4916439652442932},{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"Condition monitoring","score":0.4874546527862549},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.484894335269928},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.46825748682022095},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.4535546898841858},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42878901958465576},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36002352833747864},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.28638535737991333},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24898844957351685},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.15997809171676636},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15336158871650696},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0885050892829895}],"concepts":[{"id":"https://openalex.org/C186108316","wikidata":"https://www.wikidata.org/wiki/Q352530","display_name":"Adaptive neuro fuzzy inference system","level":4,"score":0.6430370807647705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5953264236450195},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5351776480674744},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.5300934910774231},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5236303806304932},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5214288234710693},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4916439652442932},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.4874546527862549},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.484894335269928},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.46825748682022095},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.4535546898841858},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42878901958465576},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36002352833747864},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.28638535737991333},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24898844957351685},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.15997809171676636},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15336158871650696},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0885050892829895},{"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tie.2010.2098369","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2010.2098369","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W564030374","https://openalex.org/W591732527","https://openalex.org/W1483307070","https://openalex.org/W1515591979","https://openalex.org/W1977368497","https://openalex.org/W1979195888","https://openalex.org/W1981269812","https://openalex.org/W1994217726","https://openalex.org/W2005305357","https://openalex.org/W2028340090","https://openalex.org/W2045186954","https://openalex.org/W2055849370","https://openalex.org/W2079505939","https://openalex.org/W2088463833","https://openalex.org/W2089731252","https://openalex.org/W2105762019","https://openalex.org/W2106290330","https://openalex.org/W2109418752","https://openalex.org/W2114106396","https://openalex.org/W2114646607","https://openalex.org/W2126736494","https://openalex.org/W2127342270","https://openalex.org/W2130995959","https://openalex.org/W2132301916","https://openalex.org/W2134788745","https://openalex.org/W2147104109","https://openalex.org/W2148899699","https://openalex.org/W2160337655","https://openalex.org/W2161445591","https://openalex.org/W2167801338","https://openalex.org/W2514683513","https://openalex.org/W2913642042"],"related_works":["https://openalex.org/W1510894296","https://openalex.org/W2134386692","https://openalex.org/W2082284720","https://openalex.org/W2194396582","https://openalex.org/W2116722627","https://openalex.org/W2537260108","https://openalex.org/W2379938888","https://openalex.org/W4233405330","https://openalex.org/W2792905593","https://openalex.org/W1977445474"],"abstract_inverted_index":{"Machine":[0],"prognosis":[1],"is":[2,42,59,117,135],"a":[3,19,35,109,143,148],"significant":[4],"part":[5],"of":[6,18,101,108,131],"condition-based":[7],"maintenance":[8,23],"and":[9,13,53,69,147],"intends":[10],"to":[11,33,82,96,119,124],"monitor":[12],"track":[14],"the":[15,28,84,98,102,106,121,132,139],"time":[16,99],"evolution":[17,100],"fault":[20,85,103],"so":[21],"that":[22,153],"can":[24,30],"be":[25,31],"performed":[26],"or":[27],"task":[29],"terminated":[32],"avoid":[34],"catastrophic":[36],"failure.":[37],"A":[38],"new":[39],"prognostic":[40],"method":[41,134],"developed":[43,118],"in":[44,105],"this":[45,93],"paper":[46],"using":[47,138],"adaptive":[48],"neuro-fuzzy":[49],"inference":[50],"systems":[51],"(ANFISs)":[52],"high-order":[54,89],"particle":[55,90],"filtering.":[56],"The":[57,66,88,129],"ANFIS":[58,68],"trained":[60,67],"via":[61],"machine":[62,126],"historical":[63],"failure":[64],"data.":[65],"its":[70],"modeling":[71],"noise":[72],"constitute":[73],"an":[74],"<i":[75],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[76],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">m</i>":[77],"th-order":[78],"hidden":[79],"Markov":[80,94,122],"model":[81,95,123],"describe":[83],"propagation":[86],"process.":[87],"filter":[91],"uses":[92],"predict":[97],"indicator":[104],"form":[107],"probability":[110],"density":[111],"function.":[112],"An":[113],"online":[114],"update":[115],"scheme":[116],"adapt":[120],"various":[125],"dynamics":[127],"quickly.":[128],"performance":[130],"proposed":[133],"evaluated":[136],"by":[137],"testing":[140],"data":[141],"from":[142],"cracked":[144],"carrier":[145],"plate":[146],"faulty":[149],"bearing.":[150],"Results":[151],"show":[152],"it":[154],"outperforms":[155],"classical":[156],"condition":[157],"predictors.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":21},{"year":2018,"cited_by_count":18},{"year":2017,"cited_by_count":29},{"year":2016,"cited_by_count":24},{"year":2015,"cited_by_count":18},{"year":2014,"cited_by_count":24},{"year":2013,"cited_by_count":26},{"year":2012,"cited_by_count":19}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}