{"id":"https://openalex.org/W2968698829","doi":"https://doi.org/10.1109/tim.2019.2933342","title":"Fault Diagnosis of Rotary Machine Bearings Under Inconsistent Working Conditions","display_name":"Fault Diagnosis of Rotary Machine Bearings Under Inconsistent Working Conditions","publication_year":2019,"publication_date":"2019-08-14","ids":{"openalex":"https://openalex.org/W2968698829","doi":"https://doi.org/10.1109/tim.2019.2933342","mag":"2968698829"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2019.2933342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2019.2933342","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5045475293","display_name":"Muhammad Sohaib","orcid":"https://orcid.org/0000-0003-0218-3595"},"institutions":[{"id":"https://openalex.org/I40542001","display_name":"University of Ulsan","ror":"https://ror.org/02c2f8975","country_code":"KR","type":"education","lineage":["https://openalex.org/I40542001"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Muhammad Sohaib","raw_affiliation_strings":["School of Electrical, Electronics and Computer Engineering, University of Ulsan, Ulsan, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical, Electronics and Computer Engineering, University of Ulsan, Ulsan, South Korea","institution_ids":["https://openalex.org/I40542001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026778303","display_name":"Jong-Myon Kim","orcid":"https://orcid.org/0000-0002-5185-1062"},"institutions":[{"id":"https://openalex.org/I40542001","display_name":"University of Ulsan","ror":"https://ror.org/02c2f8975","country_code":"KR","type":"education","lineage":["https://openalex.org/I40542001"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jong-Myon Kim","raw_affiliation_strings":["School of IT Convergence, University of Ulsan, Ulsan, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-5185-1062","affiliations":[{"raw_affiliation_string":"School of IT Convergence, University of Ulsan, Ulsan, South Korea","institution_ids":["https://openalex.org/I40542001"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5045475293"],"corresponding_institution_ids":["https://openalex.org/I40542001"],"apc_list":null,"apc_paid":null,"fwci":5.5593,"has_fulltext":false,"cited_by_count":76,"citation_normalized_percentile":{"value":0.96427527,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"69","issue":"6","first_page":"3334","last_page":"3347"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9970999956130981,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9911999702453613,"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/bispectrum","display_name":"Bispectrum","score":0.828605055809021},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6478573679924011},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.6153066158294678},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6010333895683289},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5855187177658081},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5336340665817261},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.5298768281936646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5179275870323181},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4987037181854248},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4594396650791168},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42881518602371216},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.39430686831474304},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.09101438522338867}],"concepts":[{"id":"https://openalex.org/C114148568","wikidata":"https://www.wikidata.org/wiki/Q2410583","display_name":"Bispectrum","level":3,"score":0.828605055809021},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6478573679924011},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.6153066158294678},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6010333895683289},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5855187177658081},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5336340665817261},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.5298768281936646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5179275870323181},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4987037181854248},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4594396650791168},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42881518602371216},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.39430686831474304},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.09101438522338867},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2019.2933342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2019.2933342","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4805935077","display_name":null,"funder_award_id":"20181510102160","funder_id":"https://openalex.org/F4320335199","funder_display_name":"Korea Institute of Energy Technology Evaluation and Planning"}],"funders":[{"id":"https://openalex.org/F4320335199","display_name":"Korea Institute of Energy Technology Evaluation and Planning","ror":"https://ror.org/02zq38y32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1994616650","https://openalex.org/W2005081781","https://openalex.org/W2013548240","https://openalex.org/W2018388266","https://openalex.org/W2035139964","https://openalex.org/W2037411704","https://openalex.org/W2053443947","https://openalex.org/W2053741029","https://openalex.org/W2076015009","https://openalex.org/W2150001221","https://openalex.org/W2199268906","https://openalex.org/W2297890608","https://openalex.org/W2324488761","https://openalex.org/W2336172209","https://openalex.org/W2471080557","https://openalex.org/W2480364715","https://openalex.org/W2485614840","https://openalex.org/W2523246573","https://openalex.org/W2534068475","https://openalex.org/W2567407101","https://openalex.org/W2736225434","https://openalex.org/W2765177954","https://openalex.org/W2767234670","https://openalex.org/W2768744233","https://openalex.org/W2771734292","https://openalex.org/W2785380284","https://openalex.org/W2791036512","https://openalex.org/W2791694051","https://openalex.org/W2796899769","https://openalex.org/W2800124572","https://openalex.org/W2804005020","https://openalex.org/W2804096023","https://openalex.org/W2899280016","https://openalex.org/W2908300307","https://openalex.org/W2916064970","https://openalex.org/W2922660557","https://openalex.org/W2940617832","https://openalex.org/W2963586744","https://openalex.org/W2964121744","https://openalex.org/W6631190155","https://openalex.org/W6681804681","https://openalex.org/W6727249380","https://openalex.org/W6748053541"],"related_works":["https://openalex.org/W2541615194","https://openalex.org/W2357592863","https://openalex.org/W2002943794","https://openalex.org/W2351984395","https://openalex.org/W2544518984","https://openalex.org/W2371303008","https://openalex.org/W2093925636","https://openalex.org/W78238107","https://openalex.org/W2122830376","https://openalex.org/W868620487"],"abstract_inverted_index":{"This":[0],"article":[1,107],"proposes":[2],"a":[3,15,63],"fault":[4],"diagnosis":[5],"(FD)":[6],"method":[7],"that":[8],"is":[9,68,89,93],"based":[10,61],"on":[11,62],"bispectrum":[12],"analysis":[13],"and":[14,39,84,92],"convolutional":[16],"neural":[17],"network":[18],"(CNN)":[19],"to":[20,70,96],"identify":[21],"bearing":[22,114],"faults":[23],"under":[24,55,125],"inconsistent":[25,56,126],"working":[26,57,127],"conditions,":[27],"such":[28],"as":[29],"high":[30],"shaft":[31],"speed":[32],"variations":[33],"with":[34,98,110],"cracks":[35],"of":[36,45,81,105,121],"multiple":[37],"scales":[38],"compound":[40],"faults.":[41],"First,":[42],"the":[43,46,75,79,111,119,122],"bispectra":[44],"vibration":[47],"signals":[48],"are":[49,108],"extracted,":[50],"which":[51,117],"exhibit":[52],"consistent":[53],"patterns":[54],"conditions.":[58,128],"Second,":[59],"CNN":[60],"stochastic":[64],"optimization":[65,88],"function":[66],"(AdaMax)":[67],"proposed":[69,123],"extract":[71],"interclass":[72],"representations":[73],"from":[74],"bispectra,":[76],"hence":[77],"reducing":[78],"overhead":[80],"feature":[82],"extraction":[83],"selection.":[85],"The":[86,102],"AdaMax":[87],"computationally":[90],"efficient":[91],"well":[94],"suited":[95],"problems":[97],"big":[99],"data":[100],"sets.":[101],"obtained":[103],"results":[104],"this":[106],"compared":[109],"current":[112],"state-of-the-art":[113],"FD":[115],"techniques,":[116],"demonstrates":[118],"superiority":[120],"model":[124]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":9}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}