{"id":"https://openalex.org/W2796687587","doi":"https://doi.org/10.1109/icacs.2018.8333495","title":"Towards bearing health prognosis using generative adversarial networks: Modeling bearing degradation","display_name":"Towards bearing health prognosis using generative adversarial networks: Modeling bearing degradation","publication_year":2018,"publication_date":"2018-02-01","ids":{"openalex":"https://openalex.org/W2796687587","doi":"https://doi.org/10.1109/icacs.2018.8333495","mag":"2796687587"},"language":"en","primary_location":{"id":"doi:10.1109/icacs.2018.8333495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacs.2018.8333495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Advancements in Computational Sciences (ICACS)","raw_type":"proceedings-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/A5082915001","display_name":"Sheraz Ali Khan","orcid":"https://orcid.org/0000-0002-9594-1457"},"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":"Sheraz Ali Khan","raw_affiliation_strings":["University of Ulsan, Ulsan, KR"],"affiliations":[{"raw_affiliation_string":"University of Ulsan, Ulsan, KR","institution_ids":["https://openalex.org/I40542001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033319277","display_name":"Alexander E. Prosvirin","orcid":"https://orcid.org/0000-0002-7943-5845"},"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":"Alexander E. Prosvirin","raw_affiliation_strings":["School of of Electrical, Electronics & Computer Engineering, University of Ulsan, Ulsan, South Korea"],"affiliations":[{"raw_affiliation_string":"School of of Electrical, Electronics & 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 of Electrical, Electronics & Computer Engineering, University of Ulsan, Ulsan, South Korea"],"affiliations":[{"raw_affiliation_string":"School of of Electrical, Electronics & Computer Engineering, University of Ulsan, Ulsan, South Korea","institution_ids":["https://openalex.org/I40542001"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5082915001"],"corresponding_institution_ids":["https://openalex.org/I40542001"],"apc_list":null,"apc_paid":null,"fwci":2.3911,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.89106739,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9983999729156494,"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/T11201","display_name":"Metallurgy and Material Forming","score":0.9812999963760376,"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/discriminator","display_name":"Discriminator","score":0.8241651058197021},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.7737643718719482},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6901533603668213},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5544527769088745},{"id":"https://openalex.org/keywords/degradation","display_name":"Degradation (telecommunications)","score":0.5365002751350403},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.508143424987793},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.4838072657585144},{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"Condition monitoring","score":0.47049757838249207},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4665534198284149},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4365687966346741},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40865352749824524},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.354783833026886},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2034028172492981}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.8241651058197021},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.7737643718719482},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6901533603668213},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5544527769088745},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.5365002751350403},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.508143424987793},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4838072657585144},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.47049757838249207},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4665534198284149},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4365687966346741},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40865352749824524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.354783833026886},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2034028172492981},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"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/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacs.2018.8333495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacs.2018.8333495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Advancements in Computational Sciences (ICACS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.49000000953674316,"display_name":"Reduced inequalities"},{"id":"https://metadata.un.org/sdg/16","score":0.4000000059604645,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1556459174","https://openalex.org/W1597576211","https://openalex.org/W1872896676","https://openalex.org/W1993880634","https://openalex.org/W1995430360","https://openalex.org/W2005523062","https://openalex.org/W2019505419","https://openalex.org/W2042311265","https://openalex.org/W2050211799","https://openalex.org/W2099471712","https://openalex.org/W2100028154","https://openalex.org/W2140055317","https://openalex.org/W2142724780","https://openalex.org/W2189521609","https://openalex.org/W2319025975","https://openalex.org/W2336172209","https://openalex.org/W2415920139","https://openalex.org/W2555992165","https://openalex.org/W2567407101","https://openalex.org/W2587247471","https://openalex.org/W2612741352","https://openalex.org/W2730958902","https://openalex.org/W2741768983","https://openalex.org/W2771498160","https://openalex.org/W2940882023","https://openalex.org/W2963373786","https://openalex.org/W4320013936","https://openalex.org/W6633355566","https://openalex.org/W6687126655","https://openalex.org/W6718379498","https://openalex.org/W6742503105","https://openalex.org/W6761550553"],"related_works":["https://openalex.org/W4293320219","https://openalex.org/W2953246223","https://openalex.org/W4283584549","https://openalex.org/W2554314924","https://openalex.org/W4288256692","https://openalex.org/W2998859928","https://openalex.org/W4381885966","https://openalex.org/W2969399009","https://openalex.org/W4398186750","https://openalex.org/W3151498616"],"abstract_inverted_index":{"Condition":[0],"based":[1],"maintenance":[2],"of":[3,16,28,34,43,67,87,126,135,151,166,182],"rotary":[4],"machines":[5],"is":[6,47,156,175],"centered":[7],"on":[8],"bearings,":[9],"as":[10],"they":[11],"are":[12,71],"the":[13,23,32,64,84,93,114,120,138,172,179],"leading":[14],"source":[15],"breakdowns":[17],"in":[18,22,110,177],"induction":[19],"motors":[20],"used":[21,72],"industry.":[24],"The":[25,40,132,144,164],"health":[26,90,154],"prognosis":[27],"bearings":[29],"primarily":[30],"involves":[31],"estimation":[33],"its":[35,52],"remaining":[36],"useful":[37],"life":[38],"(RUL).":[39],"accurate":[41],"modeling":[42,63,178],"a":[44,68,88,100,105,111,152],"bearing's":[45,89,153],"degradation":[46,65,180],"key":[48],"to":[49,73,82,118,141],"correctly":[50],"estimating":[51],"RUL.":[53],"This":[54],"paper":[55],"investigates":[56],"using":[57,158],"generative":[58,75],"adversarial":[59],"networks":[60],"(GANs)":[61],"for":[62,147],"behavior":[66,181],"bearing.":[69],"GANs":[70,136],"estimate":[74],"models,":[76],"which":[77],"can":[78],"be":[79],"sampled":[80],"directly":[81],"generate":[83],"future":[85,149],"trajectory":[86],"indicator.":[91],"In":[92],"GAN":[94,173],"framework,":[95],"two":[96],"artificial":[97],"neural":[98],"networks,":[99],"generator":[101],"network":[102,107,115,121],"G":[103,116],"and":[104],"discriminator":[106],"D,":[108],"engage":[109],"game,":[112],"where":[113],"tries":[117],"fool":[119],"D":[122],"by":[123],"generating":[124,148],"samples":[125],"data":[127],"that":[128,171],"resemble":[129],"real":[130],"data.":[131,163],"training":[133],"process":[134],"finds":[137],"Nash":[139],"equilibrium":[140],"this":[142,167],"game.":[143],"proposed":[145],"approach":[146],"trajectories":[150],"indicator":[155],"tested":[157],"publicly":[159],"available":[160],"run-to-failure":[161],"test":[162],"results":[165],"preliminary":[168],"study":[169],"indicate":[170],"framework":[174],"effective":[176],"bearings.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}