{"id":"https://openalex.org/W2974401122","doi":"https://doi.org/10.1109/coase.2019.8843078","title":"Remaining Useful Life Estimation Based on a New Convolutional and Recurrent Neural Network","display_name":"Remaining Useful Life Estimation Based on a New Convolutional and Recurrent Neural Network","publication_year":2019,"publication_date":"2019-08-01","ids":{"openalex":"https://openalex.org/W2974401122","doi":"https://doi.org/10.1109/coase.2019.8843078","mag":"2974401122"},"language":"en","primary_location":{"id":"doi:10.1109/coase.2019.8843078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coase.2019.8843078","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","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/A5032239710","display_name":"Xinyun Zhang","orcid":"https://orcid.org/0000-0002-7763-7507"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyun Zhang","raw_affiliation_strings":["The School of Electronic Information & Communications, Huazhong University of Science & Technology, Wuhan, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The School of Electronic Information & Communications, Huazhong University of Science & Technology, Wuhan, P. R. China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056041589","display_name":"Yan Dong","orcid":"https://orcid.org/0000-0002-9512-6903"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Dong","raw_affiliation_strings":["The School of Electronic Information & Communications, Huazhong University of Science & Technology, Wuhan, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The School of Electronic Information & Communications, Huazhong University of Science & Technology, Wuhan, P. R. China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001395798","display_name":"Long Wen","orcid":"https://orcid.org/0000-0002-8355-9947"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Wen","raw_affiliation_strings":["The State Key Lab. Of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Lab. Of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan, P. R. China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101664962","display_name":"Lu Fang","orcid":"https://orcid.org/0000-0003-3552-0367"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Lu","raw_affiliation_strings":["The School of Electronic Information & Communications, Huazhong University of Science & Technology, Wuhan, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The School of Electronic Information & Communications, Huazhong University of Science & Technology, Wuhan, P. R. China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100683583","display_name":"Wei Li","orcid":"https://orcid.org/0000-0002-7772-5697"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["The State Key Lab. Of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Lab. Of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan, P. R. China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":10.0907,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.99288394,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"317","last_page":"322"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9952999949455261,"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":0.9952999949455261,"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9915000200271606,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9846000075340271,"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/computer-science","display_name":"Computer science","score":0.7699111700057983},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7498038411140442},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6620882749557495},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.642254114151001},{"id":"https://openalex.org/keywords/turbofan","display_name":"Turbofan","score":0.6096723675727844},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5534480214118958},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.47493818402290344},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4591464698314667},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45191580057144165},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.44573262333869934},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44351452589035034},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.4395483434200287},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4325965642929077},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42466267943382263},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3339073657989502},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12715011835098267}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7699111700057983},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7498038411140442},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6620882749557495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.642254114151001},{"id":"https://openalex.org/C110050840","wikidata":"https://www.wikidata.org/wiki/Q654051","display_name":"Turbofan","level":2,"score":0.6096723675727844},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5534480214118958},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.47493818402290344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4591464698314667},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45191580057144165},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.44573262333869934},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44351452589035034},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.4395483434200287},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4325965642929077},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42466267943382263},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3339073657989502},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12715011835098267},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","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/coase.2019.8843078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coase.2019.8843078","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2045818742","https://openalex.org/W2063922127","https://openalex.org/W2064323378","https://openalex.org/W2104600154","https://openalex.org/W2110242546","https://openalex.org/W2127918592","https://openalex.org/W2144499799","https://openalex.org/W2155832827","https://openalex.org/W2415594836","https://openalex.org/W2617137613","https://openalex.org/W2763583057","https://openalex.org/W2768753204","https://openalex.org/W2772084711","https://openalex.org/W2789263499","https://openalex.org/W2914618626","https://openalex.org/W2915229515"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W2523437662","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456","https://openalex.org/W2766585573","https://openalex.org/W4387490624","https://openalex.org/W3152185262"],"abstract_inverted_index":{"Remaining":[0],"useful":[1],"life":[2],"(RUL)":[3],"estimation":[4,17],"is":[5,51,80],"an":[6],"important":[7],"part":[8],"of":[9,26,34,44,77,116,131],"prognostic":[10],"health":[11],"management":[12],"(PHM)":[13],"technology.":[14],"Traditional":[15],"RUL":[16,55,63],"methods":[18],"need":[19],"to":[20,112],"define":[21],"thresholds":[22,30],"with":[23],"the":[24,29,32,35,54,62,78,88,102,107,114,117,122,139,149],"help":[25],"experience,":[27],"and":[28,46,86,97,105,157,165],"affect":[31],"precision":[33],"test":[36],"results.":[37],"In":[38,110],"this":[39],"paper,":[40],"a":[41,66,72],"hybrid":[42,68,93,142],"method":[43,58],"convolutional":[45],"recurrent":[47],"neural":[48],"network":[49,69],"(CNN-RNN)":[50],"proposed":[52,91,118,140],"for":[53],"estimation.":[56],"This":[57],"can":[59,100],"accurately":[60],"predict":[61],"by":[64,83],"using":[65],"trained":[67],"without":[70],"setting":[71],"threshold.":[73],"The":[74,90,134],"prediction":[75],"accuracy":[76],"model":[79,94,143],"further":[81],"improved":[82],"processing,":[84],"clustering,":[85],"classifying":[87],"data.":[89],"CNN-RNN":[92,141],"combines":[95],"CNN":[96],"RNN,":[98],"it":[99],"extract":[101],"local":[103],"features":[104],"capture":[106],"degradation":[108],"process.":[109],"order":[111],"show":[113,137],"effectiveness":[115],"approach,":[119],"tests":[120],"on":[121,162],"NASA":[123],"Commercial":[124],"Modular":[125],"Aero-Propulsion":[126],"System":[127],"Simulation":[128],"(C-MAPSS)":[129],"dataset":[130],"turbofan":[132],"engine.":[133],"experimental":[135],"results":[136],"that":[138],"achieves":[144],"better":[145],"score":[146],"values":[147],"than":[148],"Multilayer":[150],"Perceptron":[151],"(MLP),":[152],"Support":[153],"Vector":[154],"Regression":[155],"(SVR)":[156],"Convolutional":[158],"Neural":[159],"Network":[160],"(CNN)":[161],"FDOOI,":[163],"FD003":[164],"FD004":[166],"data":[167],"sets.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}