{"id":"https://openalex.org/W3007621322","doi":"https://doi.org/10.1109/ssci44817.2019.9002764","title":"A Comparative Study on the Data-driven Based Prognostic Approaches for RUL of Rolling Bearings","display_name":"A Comparative Study on the Data-driven Based Prognostic Approaches for RUL of Rolling Bearings","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3007621322","doi":"https://doi.org/10.1109/ssci44817.2019.9002764","mag":"3007621322"},"language":"en","primary_location":{"id":"doi:10.1109/ssci44817.2019.9002764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci44817.2019.9002764","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5033119399","display_name":"Xiaojie Zhai","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojie Zhai","raw_affiliation_strings":["State Key Lab of Rail Traffic Control & Safety, Beijing Jiaotong University School of traffic and transportation, Beijing Jiaotong University Beijing Research Center of Urban Traffic Information Intelligent Sensing and Service Technologies, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of Rail Traffic Control & Safety, Beijing Jiaotong University School of traffic and transportation, Beijing Jiaotong University Beijing Research Center of Urban Traffic Information Intelligent Sensing and Service Technologies, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051900939","display_name":"Xiukun Wei","orcid":"https://orcid.org/0000-0003-0341-966X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiukun Wei","raw_affiliation_strings":["State Key Lab of Rail Traffic Control & Safety, Beijing Jiaotong University School of traffic and transportation, Beijing Jiaotong University Beijing Research Center of Urban Traffic Information Intelligent Sensing and Service Technologies, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of Rail Traffic Control & Safety, Beijing Jiaotong University School of traffic and transportation, Beijing Jiaotong University Beijing Research Center of Urban Traffic Information Intelligent Sensing and Service Technologies, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024909097","display_name":"Jihong Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210161003","display_name":"Qingdao Center of Resource Chemistry and New Materials","ror":"https://ror.org/05x85k702","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210089297","https://openalex.org/I4210161003"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jihong Yang","raw_affiliation_strings":["CRRC Qingdao Sifang Co., Ltd., Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CRRC Qingdao Sifang Co., Ltd., Qingdao, China","institution_ids":["https://openalex.org/I4210161003"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4448,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.63723403,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1751","last_page":"1755"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.9995999932289124,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9991999864578247,"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/T11201","display_name":"Metallurgy and Material Forming","score":0.9970999956130981,"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/computer-science","display_name":"Computer science","score":0.5559436082839966},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.42040765285491943},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3246819078922272},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.07446685433387756}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5559436082839966},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.42040765285491943},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3246819078922272},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.07446685433387756}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci44817.2019.9002764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci44817.2019.9002764","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Responsible consumption and production","score":0.550000011920929,"id":"https://metadata.un.org/sdg/12"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1999072074","https://openalex.org/W2033800551","https://openalex.org/W2054972225","https://openalex.org/W2066593543","https://openalex.org/W2074148881","https://openalex.org/W2110007571","https://openalex.org/W2114106396","https://openalex.org/W2135449931","https://openalex.org/W2157457477","https://openalex.org/W2318967438","https://openalex.org/W2331534005","https://openalex.org/W6680383090"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{"With":[0],"the":[1,28,31,44,47,58,64,88,117,122,129,133],"condition":[2,82],"monitoring":[3,83],"equipment":[4],"becoming":[5],"more":[6,85],"sophisticated,":[7],"data-driven":[8],"based":[9,49,77],"prognostic":[10,24,75],"approaches":[11,25],"for":[12],"remaining":[13,102],"useful":[14,103],"life":[15,104],"(RUL)":[16],"are":[17,61],"emerging.":[18],"This":[19],"paper":[20],"introduces":[21],"three":[22],"classical":[23],"and":[26,81,97],"verifies":[27],"effectiveness":[29],"through":[30],"whole-life":[32],"cycle":[33],"experimental":[34],"data":[35],"of":[36,46,90,94,124],"degenerated":[37],"rolling":[38],"bearings.":[39],"The":[40,74],"result":[41],"shows":[42],"that":[43],"prediction":[45,105,127],"methods":[48],"on":[50,78],"probability":[51],"statistics":[52],"will":[53,99],"be":[54,68],"greatly":[55],"affected,":[56],"if":[57],"prior":[59],"parameters":[60],"inaccurate.":[62],"And":[63],"degradation":[65],"model":[66],"cannot":[67],"adapted":[69],"to":[70,120,131],"individual":[71],"bearing":[72],"accurately.":[73],"method":[76],"artificial":[79],"intelligence":[80],"is":[84,128],"accurate":[86],"in":[87],"case":[89],"a":[91,101],"small":[92],"number":[93],"training":[95],"samples,":[96],"it":[98],"output":[100],"interval":[106],"with":[107,113],"higher":[108],"reliability.":[109],"Therefore,":[110],"by":[111],"combining":[112],"other":[114],"models,":[115],"improving":[116],"intelligent":[118],"algorithm":[119],"enhance":[121],"accuracy":[123],"its":[125],"RUL":[126],"key":[130],"solve":[132],"problem":[134],"about":[135],"online":[136],"prognostic.":[137]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
