{"id":"https://openalex.org/W4210799828","doi":"https://doi.org/10.1109/safeprocess52771.2021.9693675","title":"Fault Identification and Remaining Useful Life Prediction for Complex Equipment under Multiple Fault Modes","display_name":"Fault Identification and Remaining Useful Life Prediction for Complex Equipment under Multiple Fault Modes","publication_year":2021,"publication_date":"2021-12-17","ids":{"openalex":"https://openalex.org/W4210799828","doi":"https://doi.org/10.1109/safeprocess52771.2021.9693675"},"language":"en","primary_location":{"id":"doi:10.1109/safeprocess52771.2021.9693675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/safeprocess52771.2021.9693675","pdf_url":null,"source":{"id":"https://openalex.org/S4363605570","display_name":"2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS)","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/A5024645510","display_name":"Jiapeng Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiapeng Cui","raw_affiliation_strings":["University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering,Beijing,China","Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering,Beijing,China","institution_ids":["https://openalex.org/I92403157"]},{"raw_affiliation_string":"Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006335742","display_name":"Kaixiang Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaixiang Peng","raw_affiliation_strings":["University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering,Beijing,China","Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering,Beijing,China","institution_ids":["https://openalex.org/I92403157"]},{"raw_affiliation_string":"Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042195713","display_name":"Pengxue Lang","orcid":null},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengxue Lang","raw_affiliation_strings":["University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering,Beijing,China","Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering,Beijing,China","institution_ids":["https://openalex.org/I92403157"]},{"raw_affiliation_string":"Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086816369","display_name":"Shuai Lu","orcid":"https://orcid.org/0000-0002-5753-5327"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Lu","raw_affiliation_strings":["University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering,Beijing,China","Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering,Beijing,China","institution_ids":["https://openalex.org/I92403157"]},{"raw_affiliation_string":"Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024645510"],"corresponding_institution_ids":["https://openalex.org/I92403157"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27570674,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"116","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":0.9890999794006348,"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":0.9890999794006348,"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":0.9664999842643738,"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":0.9510999917984009,"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/dynamic-time-warping","display_name":"Dynamic time warping","score":0.6793112754821777},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6630334258079529},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6240841150283813},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6045769453048706},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5911185145378113},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5569975972175598},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5056564807891846},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4955369234085083},{"id":"https://openalex.org/keywords/prognostics","display_name":"Prognostics","score":0.4552352726459503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4038131833076477},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3975699245929718},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3539457619190216},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32080990076065063},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2987784147262573}],"concepts":[{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.6793112754821777},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6630334258079529},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6240841150283813},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6045769453048706},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5911185145378113},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5569975972175598},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5056564807891846},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4955369234085083},{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.4552352726459503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4038131833076477},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3975699245929718},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3539457619190216},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32080990076065063},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2987784147262573},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/safeprocess52771.2021.9693675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/safeprocess52771.2021.9693675","pdf_url":null,"source":{"id":"https://openalex.org/S4363605570","display_name":"2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS)","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":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W350034163","https://openalex.org/W1970477712","https://openalex.org/W2042311265","https://openalex.org/W2055873761","https://openalex.org/W2078263418","https://openalex.org/W2429285480","https://openalex.org/W2471161958","https://openalex.org/W2516566105","https://openalex.org/W2544905596","https://openalex.org/W2546933409","https://openalex.org/W2612484771","https://openalex.org/W2772550576","https://openalex.org/W2773549135","https://openalex.org/W2902700103","https://openalex.org/W2932010661","https://openalex.org/W2947621394","https://openalex.org/W2956342231","https://openalex.org/W2976132861","https://openalex.org/W3036545762","https://openalex.org/W3039311102","https://openalex.org/W6780725566"],"related_works":["https://openalex.org/W2310476526","https://openalex.org/W3213192587","https://openalex.org/W2144291498","https://openalex.org/W2535730979","https://openalex.org/W2370073012","https://openalex.org/W4386567722","https://openalex.org/W2168646784","https://openalex.org/W2030958945","https://openalex.org/W2466930957","https://openalex.org/W3182014137"],"abstract_inverted_index":{"To":[0],"ensure":[1],"the":[2,12,15,21,37,41,100,102,117,126],"safe":[3],"operation":[4],"of":[5,14,23,27],"complex":[6],"equipment":[7],"and":[8,20,49,96],"specify":[9],"maintenance":[10],"strategies,":[11],"prediction":[13,51,128],"remaining":[16],"useful":[17],"life":[18],"(RUL)":[19],"identification":[22],"failure":[24,55,75],"modes":[25,39,56],"are":[26],"great":[28],"significance.":[29],"Generally,":[30],"it":[31],"is":[32,57,68,90,104],"difficult":[33],"to":[34,72,92],"directly":[35],"differentiate":[36],"fault":[38,47],"from":[40],"raw":[42],"data.":[43],"Thus,":[44],"a":[45,79,85,121],"novel":[46],"clustering":[48],"RUL":[50],"framework":[52,119],"under":[53],"multiple":[54,74],"proposed":[58,118],"in":[59],"this":[60],"paper.":[61],"First,":[62],"dynamic":[63],"time":[64],"warping":[65],"(DTW)":[66],"distance":[67],"combined":[69],"with":[70,84,125],"k-medoids":[71],"identify":[73],"modes.":[76],"Following":[77],"that,":[78],"convolutional":[80],"neural":[81],"network":[82],"connecting":[83],"long":[86],"short-term":[87],"memory":[88],"(CNN-LSTM)":[89],"constructed":[91],"extract":[93],"hidden":[94],"features":[95],"predict":[97],"RUL.":[98],"In":[99],"end,":[101],"experiment":[103],"conducted":[105],"on":[106],"an":[107],"engine":[108],"dataset":[109],"provided":[110],"by":[111],"NASA.":[112],"The":[113],"results":[114],"show":[115],"that":[116],"has":[120],"better":[122],"performance":[123],"compared":[124],"competitive":[127],"methods.":[129]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
