{"id":"https://openalex.org/W2775106354","doi":"https://doi.org/10.1080/08839514.2017.1413066","title":"A Hybrid Genetic Algorithm and Back-Propagation Classifier for Gearbox Fault Diagnosis","display_name":"A Hybrid Genetic Algorithm and Back-Propagation Classifier for Gearbox Fault Diagnosis","publication_year":2017,"publication_date":"2017-09-14","ids":{"openalex":"https://openalex.org/W2775106354","doi":"https://doi.org/10.1080/08839514.2017.1413066","mag":"2775106354"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2017.1413066","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2017.1413066","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5062865229","display_name":"Sunil Tyagi","orcid":"https://orcid.org/0000-0001-5897-7955"},"institutions":[{"id":"https://openalex.org/I156406944","display_name":"Defence Institute of Advanced Technology","ror":"https://ror.org/05qpbfx18","country_code":"IN","type":"education","lineage":["https://openalex.org/I156406944"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sunil Tyagi","raw_affiliation_strings":["Department of Mechanical Engineering, Defense Institute of Advance Technology, Girinagar, Pune, India"],"raw_orcid":"https://orcid.org/0000-0001-5897-7955","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Defense Institute of Advance Technology, Girinagar, Pune, India","institution_ids":["https://openalex.org/I156406944"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023484456","display_name":"S.K. Panigrahi","orcid":null},"institutions":[{"id":"https://openalex.org/I156406944","display_name":"Defence Institute of Advanced Technology","ror":"https://ror.org/05qpbfx18","country_code":"IN","type":"education","lineage":["https://openalex.org/I156406944"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"S. K. Panigrahi","raw_affiliation_strings":["Department of Mechanical Engineering, Defense Institute of Advance Technology, Girinagar, Pune, India"],"raw_orcid":"https://orcid.org/0000-0001-6624-0988","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Defense Institute of Advance Technology, Girinagar, Pune, India","institution_ids":["https://openalex.org/I156406944"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023484456"],"corresponding_institution_ids":["https://openalex.org/I156406944"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":1.8365,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.8666794,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"31","issue":"7-8","first_page":"593","last_page":"612"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9976000189781189,"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":0.9976000189781189,"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":0.9878000020980835,"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/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.9854999780654907,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7637524604797363},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7549947500228882},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6478251814842224},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6230151653289795},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.5673011541366577},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5551884174346924},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.4771970212459564},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4724857211112976},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.42119863629341125},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.41682398319244385},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.41450512409210205},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3371598422527313},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17093074321746826},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.11595335602760315},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.09995168447494507}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7637524604797363},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7549947500228882},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6478251814842224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6230151653289795},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.5673011541366577},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5551884174346924},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.4771970212459564},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4724857211112976},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.42119863629341125},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.41682398319244385},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.41450512409210205},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3371598422527313},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17093074321746826},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.11595335602760315},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.09995168447494507},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2017.1413066","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2017.1413066","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3e56afbc8cbe4393902f2e8331693662","is_oa":false,"landing_page_url":"https://doaj.org/article/3e56afbc8cbe4393902f2e8331693662","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 31, Iss 7-8, Pp 593-612 (2017)","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W618152275","https://openalex.org/W618561231","https://openalex.org/W1659842140","https://openalex.org/W1856861702","https://openalex.org/W1966237354","https://openalex.org/W1968182870","https://openalex.org/W1980811222","https://openalex.org/W2002016471","https://openalex.org/W2005934359","https://openalex.org/W2008598341","https://openalex.org/W2034790739","https://openalex.org/W2037411704","https://openalex.org/W2041124359","https://openalex.org/W2059404375","https://openalex.org/W2071908367","https://openalex.org/W2074724805","https://openalex.org/W2087299198","https://openalex.org/W2116508707","https://openalex.org/W2132984323","https://openalex.org/W2149854044","https://openalex.org/W2150313473","https://openalex.org/W2158442843","https://openalex.org/W2325535142","https://openalex.org/W2396076036","https://openalex.org/W2497275036","https://openalex.org/W2622332645","https://openalex.org/W2942524707","https://openalex.org/W4210440648","https://openalex.org/W4301052031"],"related_works":["https://openalex.org/W2782295999","https://openalex.org/W2162306796","https://openalex.org/W1970292246","https://openalex.org/W2016162169","https://openalex.org/W4247952185","https://openalex.org/W1642462315","https://openalex.org/W2015118744","https://openalex.org/W2005619368","https://openalex.org/W1879092539","https://openalex.org/W2526155427"],"abstract_inverted_index":{"An":[0],"Artificial":[1],"Neural":[2],"Network":[3],"(ANN)":[4],"classifier":[5,113],"trained":[6,126,138],"by":[7,127,139,162],"a":[8,41],"hybrid":[9,60,112,129,172],"GA-BP":[10,59,111,128,171],"method":[11,130],"for":[12],"diagnosis":[13],"of":[14,30,40,77,155,169],"gear":[15,117],"faults":[16,51],"is":[17,137,173],"presented":[18],"here":[19],"that":[20,44,109,123,136,150],"can":[21,114],"be":[22],"incorporated":[23],"in":[24,47,68,79],"an":[25],"online":[26],"fault":[27],"diagnostic":[28],"system":[29],"vital":[31],"gearboxes.":[32],"The":[33],"distinctive":[34],"features":[35,73,87],"obtained":[36],"from":[37],"vibration":[38,64,158],"signals":[39,65,159],"running":[42],"gearbox;":[43],"was":[45,107,120,147],"operated":[46],"normal":[48],"and":[49,82,92],"with":[50,85],"induced":[52],"conditions":[53],"were":[54,66,95],"used":[55],"to":[56,97,153],"feed":[57,98],"the":[58,99,103,110,124,157,170],"classifier.":[61,100],"Time":[62],"domain":[63,81],"divided":[67],"40segments.":[69],"From":[70],"each":[71],"segment":[72],"such":[74,88],"as":[75,89],"magnitude":[76],"peaks":[78],"time":[80],"spectrum":[83],"along":[84],"statistical":[86],"central":[90],"moments":[91],"standard":[93,140],"deviations":[94],"extracted":[96],"Based":[101],"on":[102],"experimental":[104],"results":[105],"it":[106,146],"shown":[108,122,149],"successfully":[115],"identify":[116],"condition.":[118],"It":[119],"also":[121,148],"network":[125],"performs":[131],"much":[132],"better":[133],"than":[134],"ANN":[135],"BP":[141],"or":[142],"GA":[143],"individually.":[144],"Further,":[145],"if":[151],"prior":[152],"extraction":[154],"features;":[156],"are":[160],"pre-processed":[161],"Discrete":[163],"Wavelet":[164],"Transform":[165],"(DWT)":[166],"then":[167],"efficacy":[168],"significantly":[174],"enhanced.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}