{"id":"https://openalex.org/W2744632264","doi":"https://doi.org/10.1109/access.2017.2735966","title":"Remaining Useful Life Prediction for a Machine With Multiple Dependent Features Based on Bayesian Dynamic Linear Model and Copulas","display_name":"Remaining Useful Life Prediction for a Machine With Multiple Dependent Features Based on Bayesian Dynamic Linear Model and Copulas","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2744632264","doi":"https://doi.org/10.1109/access.2017.2735966","mag":"2744632264"},"language":"en","primary_location":{"id":"doi:10.1109/access.2017.2735966","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2735966","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2017.2735966","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088929641","display_name":"Fuqiang Sun","orcid":"https://orcid.org/0000-0002-7667-7363"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuqiang Sun","raw_affiliation_strings":["Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7667-7363","affiliations":[{"raw_affiliation_string":"Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100387148","display_name":"Ning Wang","orcid":"https://orcid.org/0000-0002-4902-5589"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Wang","raw_affiliation_strings":["Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100606922","display_name":"Xiaoyang Li","orcid":"https://orcid.org/0000-0002-4046-2934"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyang Li","raw_affiliation_strings":["Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4046-2934","affiliations":[{"raw_affiliation_string":"Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101657644","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0002-7754-6058"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7754-6058","affiliations":[{"raw_affiliation_string":"Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.3068,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.93444304,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"5","issue":null,"first_page":"16277","last_page":"16287"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9851999878883362,"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/copula","display_name":"Copula (linguistics)","score":0.6765074133872986},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6655092239379883},{"id":"https://openalex.org/keywords/gamma-process","display_name":"Gamma process","score":0.6082334518432617},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5759250521659851},{"id":"https://openalex.org/keywords/degradation","display_name":"Degradation (telecommunications)","score":0.5408483147621155},{"id":"https://openalex.org/keywords/cumulative-distribution-function","display_name":"Cumulative distribution function","score":0.5228769779205322},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4806881844997406},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.44304358959198},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35820090770721436},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34025973081588745},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.258775919675827},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.25199487805366516},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.234412282705307},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.2278367578983307}],"concepts":[{"id":"https://openalex.org/C17618745","wikidata":"https://www.wikidata.org/wiki/Q207509","display_name":"Copula (linguistics)","level":2,"score":0.6765074133872986},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6655092239379883},{"id":"https://openalex.org/C79495835","wikidata":"https://www.wikidata.org/wiki/Q5520315","display_name":"Gamma process","level":2,"score":0.6082334518432617},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5759250521659851},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.5408483147621155},{"id":"https://openalex.org/C103784038","wikidata":"https://www.wikidata.org/wiki/Q386228","display_name":"Cumulative distribution function","level":3,"score":0.5228769779205322},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4806881844997406},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.44304358959198},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35820090770721436},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34025973081588745},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.258775919675827},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25199487805366516},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.234412282705307},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2278367578983307},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2017.2735966","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2735966","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e72fdbd0b48b4f1f8b9c1f33fbc41704","is_oa":true,"landing_page_url":"https://doaj.org/article/e72fdbd0b48b4f1f8b9c1f33fbc41704","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 5, Pp 16277-16287 (2017)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2017.2735966","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2735966","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production","score":0.5799999833106995}],"awards":[{"id":"https://openalex.org/G1714187255","display_name":null,"funder_award_id":"51405009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G92370711","display_name":null,"funder_award_id":"61603018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W81739656","https://openalex.org/W186039566","https://openalex.org/W1964039725","https://openalex.org/W1980363510","https://openalex.org/W2004839758","https://openalex.org/W2029536321","https://openalex.org/W2033800551","https://openalex.org/W2040090724","https://openalex.org/W2053621553","https://openalex.org/W2055300911","https://openalex.org/W2055873761","https://openalex.org/W2064228310","https://openalex.org/W2066212288","https://openalex.org/W2074108366","https://openalex.org/W2089396560","https://openalex.org/W2116870707","https://openalex.org/W2119436275","https://openalex.org/W2151926297","https://openalex.org/W2192551759","https://openalex.org/W2300031772","https://openalex.org/W2345145213","https://openalex.org/W2507039649","https://openalex.org/W2508434657","https://openalex.org/W2513769405","https://openalex.org/W2547400235","https://openalex.org/W2593519057","https://openalex.org/W2610359854","https://openalex.org/W4240810135","https://openalex.org/W4388290870","https://openalex.org/W6603340984"],"related_works":["https://openalex.org/W2178773193","https://openalex.org/W4387164954","https://openalex.org/W4399357228","https://openalex.org/W3124913437","https://openalex.org/W4292179272","https://openalex.org/W4213267843","https://openalex.org/W1980528650","https://openalex.org/W2168519368","https://openalex.org/W3102213005","https://openalex.org/W3122621839"],"abstract_inverted_index":{"Degradation":[0],"modeling":[1,44,196],"and":[2,20,63,97,131,197],"remaining":[3],"useful":[4],"life":[5],"(RUL)":[6],"prediction":[7],"for":[8,138,192],"products":[9],"with":[10],"multiple":[11,34],"degradation":[12,35,43,61,85,117,140,177,195],"features":[13,36],"are":[14,125,149,179],"hot":[15],"topics":[16],"in":[17],"the":[18,31,48,58,64,71,83,93,102,108,112,116,122,127,155,163,193],"prognostic":[19],"health":[21],"management.":[22],"The":[23],"key":[24],"to":[25,29,56,69,81,161,181],"this":[26,39],"problem":[27],"is":[28,54,67,79,158],"describe":[30],"dependence":[32,72],"among":[33,73],"effectively.":[37],"In":[38],"paper,":[40],"a":[41,171,189],"multivariate":[42,84,194],"approach":[45],"based":[46],"on":[47],"Bayesian":[49],"dynamic":[50],"linear":[51,94],"model":[52,96,103,113],"(BDLM)":[53],"proposed":[55,184],"calculate":[57],"RULs":[59],"of":[60,119,136,152,170],"features,":[62,178],"Copula":[65,156],"function":[66,130,134,157],"employed":[68],"capture":[70],"RUL":[74,137,147,198],"distributions.":[75],"A":[76],"combined":[77],"BDLM":[78],"used":[80],"establish":[82],"model,":[86],"which":[87,174],"includes":[88],"two":[89,176],"typical":[90],"BDLMs,":[91],"namely,":[92],"growth":[95],"seasonal":[98],"factors":[99],"model.":[100],"After":[101],"parameters":[104],"get":[105],"calibrated":[106],"by":[107],"maximum":[109],"likelihood":[110],"estimation,":[111],"can":[114,142],"predict":[115],"process":[118],"features.":[120],"Once":[121],"failure":[123],"thresholds":[124],"given,":[126],"probability":[128],"density":[129],"cumulative":[132],"distribution":[133],"(CDF)":[135],"each":[139,153],"feature":[141],"be":[143],"obtained.":[144],"Since":[145],"these":[146],"distributions":[148],"not":[150],"independent":[151],"other,":[154],"adopted":[159],"herein":[160],"couple":[162],"CDFs.":[164],"Finally,":[165],"some":[166],"practical":[167],"testing":[168],"data":[169],"microwave":[172],"component,":[173],"has":[175],"utilized":[180],"validate":[182],"our":[183],"method.":[185],"This":[186],"paper":[187],"provides":[188],"new":[190],"idea":[191],"prediction.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}