{"id":"https://openalex.org/W4388279773","doi":"https://doi.org/10.1109/safeprocess58597.2023.10295921","title":"A Probabilistic Bayesian Transformer for Bearings Remaining Useful Life Prediction","display_name":"A Probabilistic Bayesian Transformer for Bearings Remaining Useful Life Prediction","publication_year":2023,"publication_date":"2023-09-22","ids":{"openalex":"https://openalex.org/W4388279773","doi":"https://doi.org/10.1109/safeprocess58597.2023.10295921"},"language":"en","primary_location":{"id":"doi:10.1109/safeprocess58597.2023.10295921","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/safeprocess58597.2023.10295921","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5059141897","display_name":"Huachao Peng","orcid":"https://orcid.org/0009-0008-8068-193X"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huachao Peng","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics,College of Automation Engineering,Nanjing,China","College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics,College of Automation Engineering,Nanjing,China","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bin Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Jiang","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics,College of Automation Engineering,Nanjing,China","College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics,College of Automation Engineering,Nanjing,China","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047094357","display_name":"Zehui Mao","orcid":"https://orcid.org/0000-0002-3189-5359"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zehui Mao","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics,College of Automation Engineering,Nanjing,China","College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics,College of Automation Engineering,Nanjing,China","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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":0.9976000189781189,"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/T13891","display_name":"Engineering Diagnostics and Reliability","score":0.9797999858856201,"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"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9595999717712402,"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/prognostics","display_name":"Prognostics","score":0.8167099356651306},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6818575263023376},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6320956349372864},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.5936909317970276},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5463944673538208},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5353591442108154},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5345759987831116},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.49727776646614075},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.49021798372268677},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4712650775909424},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.46531251072883606},{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"Condition monitoring","score":0.428882896900177},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.42037373781204224},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2424001693725586},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13190549612045288}],"concepts":[{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.8167099356651306},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6818575263023376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6320956349372864},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.5936909317970276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5463944673538208},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5353591442108154},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5345759987831116},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.49727776646614075},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.49021798372268677},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4712650775909424},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.46531251072883606},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.428882896900177},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.42037373781204224},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2424001693725586},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13190549612045288},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/safeprocess58597.2023.10295921","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/safeprocess58597.2023.10295921","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1494192115","https://openalex.org/W2471161958","https://openalex.org/W2603225712","https://openalex.org/W2905189977","https://openalex.org/W2910171846","https://openalex.org/W2927135077","https://openalex.org/W2945413072","https://openalex.org/W2951266961","https://openalex.org/W2965563166","https://openalex.org/W2981973403","https://openalex.org/W2999663439","https://openalex.org/W3017805480","https://openalex.org/W3021048621","https://openalex.org/W3033580259","https://openalex.org/W3045162186","https://openalex.org/W3089341989","https://openalex.org/W3118069256","https://openalex.org/W3119649142","https://openalex.org/W3130100540","https://openalex.org/W3160886584","https://openalex.org/W3173407600","https://openalex.org/W4226397853","https://openalex.org/W4285186957","https://openalex.org/W4292622317","https://openalex.org/W4296445039","https://openalex.org/W4312641439","https://openalex.org/W4315784968","https://openalex.org/W6736412012","https://openalex.org/W6758366860","https://openalex.org/W6764214684"],"related_works":["https://openalex.org/W2908973203","https://openalex.org/W2801712269","https://openalex.org/W1872896676","https://openalex.org/W2156691445","https://openalex.org/W2045186954","https://openalex.org/W3000986292","https://openalex.org/W1502469213","https://openalex.org/W2123638926","https://openalex.org/W2568310397","https://openalex.org/W2962769357"],"abstract_inverted_index":{"Deep-learning":[0],"(DL)":[1],"have":[2],"been":[3],"widely":[4],"applied":[5],"to":[6,29,35,56,70,90,114],"fault":[7,51],"prognostic":[8,52],"based":[9],"on":[10,109],"sufficient":[11],"condition":[12],"monitoring":[13,77],"data.":[14,78,126],"However,":[15],"when":[16],"given":[17],"limited":[18,125],"training":[19],"data,":[20],"most":[21],"existing":[22],"methods":[23],"with":[24],"fixed,":[25],"deterministic":[26],"parameters":[27],"fail":[28],"address":[30],"prognostics":[31],"uncertainty":[32],"and":[33,37,93,118],"lead":[34],"over-fitting":[36],"poor":[38],"generalization.":[39],"To":[40],"overcome":[41],"these":[42],"problems,":[43],"a":[44],"probabilistic":[45],"Bayesian":[46,86],"Temporal":[47],"Convolutional":[48],"Transformer":[49,69],"(BTCT)-based":[50],"framework":[53],"is":[54,82],"developed":[55],"RUL":[57,95],"prediction.":[58],"The":[59],"BTCT":[60],"model":[61,81],"first":[62],"integrates":[63],"temporal":[64],"convolutional":[65],"network":[66],"(TCN)":[67],"into":[68,84],"extract":[71],"multiscale":[72],"features":[73],"directly":[74],"from":[75],"raw":[76],"Then,":[79],"the":[80,85,116,121],"integrated":[83],"deep":[87],"learning":[88],"(BDL)":[89],"learn":[91],"uncertainties":[92],"provide":[94],"prediction":[96],"confidence":[97],"intervals":[98],"(CIs)":[99],"at":[100],"certain":[101],"level.":[102],"Finally,":[103],"comparative":[104],"experiments":[105],"are":[106],"carried":[107],"out":[108],"an":[110],"open-sourced":[111],"bearings":[112],"datasets":[113],"demonstrate":[115],"accuracy":[117],"superiority":[119],"of":[120],"proposed":[122],"approaches":[123],"under":[124]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}