{"id":"https://openalex.org/W2951288123","doi":"https://doi.org/10.1142/s0218001420510076","title":"Diamond-Coated Mechanical Seal Remaining Useful Life Prediction Based on Convolution Neural Network","display_name":"Diamond-Coated Mechanical Seal Remaining Useful Life Prediction Based on Convolution Neural Network","publication_year":2019,"publication_date":"2019-06-20","ids":{"openalex":"https://openalex.org/W2951288123","doi":"https://doi.org/10.1142/s0218001420510076","mag":"2951288123"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001420510076","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001420510076","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5101831798","display_name":"Zhibin Lin","orcid":"https://orcid.org/0000-0002-2891-8337"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhibin Lin","raw_affiliation_strings":["School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.\u00a0R.\u00a0China"],"raw_orcid":"https://orcid.org/0000-0002-2891-8337","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055401422","display_name":"Hongli Gao","orcid":"https://orcid.org/0000-0002-9288-4418"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongli Gao","raw_affiliation_strings":["School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043194723","display_name":"Erqing Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Erqing Zhang","raw_affiliation_strings":["State Key Laboratory of Tribology, Tsinghua University, Peking 100084, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Tribology, Tsinghua University, Peking 100084, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011352023","display_name":"Weiqing Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiqing Cao","raw_affiliation_strings":["School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045584566","display_name":"Kesi Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kesi Li","raw_affiliation_strings":["School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101831798"],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":0.3285,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.56811948,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"34","issue":"05","first_page":"2051007","last_page":"2051007"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9970999956130981,"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":0.9970999956130981,"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/T11557","display_name":"Lubricants and Their Additives","score":0.9764000177383423,"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/T10188","display_name":"Advanced machining processes and optimization","score":0.96670001745224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6087968945503235},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6025369167327881},{"id":"https://openalex.org/keywords/seal","display_name":"Seal (emblem)","score":0.582866907119751},{"id":"https://openalex.org/keywords/diamond","display_name":"Diamond","score":0.5589444637298584},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.526055097579956},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.5233446955680847},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.46634358167648315},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.45603784918785095},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.42256516218185425},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40432482957839966},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.31653842329978943},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.2583475708961487},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25512611865997314},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2421703040599823},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.2404729425907135}],"concepts":[{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6087968945503235},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6025369167327881},{"id":"https://openalex.org/C2777755289","wikidata":"https://www.wikidata.org/wiki/Q162919","display_name":"Seal (emblem)","level":2,"score":0.582866907119751},{"id":"https://openalex.org/C2776921476","wikidata":"https://www.wikidata.org/wiki/Q5283","display_name":"Diamond","level":2,"score":0.5589444637298584},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.526055097579956},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.5233446955680847},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.46634358167648315},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.45603784918785095},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.42256516218185425},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40432482957839966},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.31653842329978943},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.2583475708961487},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25512611865997314},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2421703040599823},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.2404729425907135},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"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:10.1142/s0218001420510076","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001420510076","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"display_name":"Responsible consumption and production","id":"https://metadata.un.org/sdg/12"}],"awards":[{"id":"https://openalex.org/G5674741121","display_name":null,"funder_award_id":"2682016CX033","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W610863331","https://openalex.org/W1532221965","https://openalex.org/W1887369574","https://openalex.org/W1978366602","https://openalex.org/W1980066084","https://openalex.org/W2053443947","https://openalex.org/W2066512221","https://openalex.org/W2095168232","https://openalex.org/W2096874867","https://openalex.org/W2106391797","https://openalex.org/W2204168354","https://openalex.org/W2255466643","https://openalex.org/W2286877141","https://openalex.org/W2415594836","https://openalex.org/W2418691539","https://openalex.org/W2485614840","https://openalex.org/W2521042034","https://openalex.org/W2595657631","https://openalex.org/W2606004785","https://openalex.org/W2737617578","https://openalex.org/W2815862320","https://openalex.org/W4205518425","https://openalex.org/W4240067071"],"related_works":["https://openalex.org/W4380433113","https://openalex.org/W4386072068","https://openalex.org/W252339960","https://openalex.org/W2390529043","https://openalex.org/W2378320433","https://openalex.org/W2358343511","https://openalex.org/W2051877971","https://openalex.org/W1970117064","https://openalex.org/W1787170397","https://openalex.org/W4292347844"],"abstract_inverted_index":{"Reliable":[0],"remaining":[1],"useful":[2],"life":[3],"(RUL)":[4],"prediction":[5,183],"of":[6,12,35,54,84,88,173],"industrial":[7],"equipment":[8],"key":[9],"components":[10,40],"is":[11,33,53,75],"considerable":[13],"importance":[14],"in":[15,41,157],"condition-based":[16],"maintenance":[17],"to":[18,77,116,124,132,140,155,188],"avoid":[19],"catastrophic":[20],"failure,":[21],"promote":[22],"reliability":[23],"and":[24,46,99,137],"reduce":[25],"cost":[26],"during":[27],"the":[28,36,51,59,94,101,118,126,165,171],"production.":[29],"Diamond-coated":[30],"mechanical":[31,64,121,175,191],"seal":[32,65,134,176],"one":[34],"most":[37],"critical":[38,55],"wearing":[39],"petroleum":[42],"chemical,":[43],"nuclear":[44],"power":[45],"other":[47,189],"process":[48,103,136],"industries.":[49],"Estimating":[50],"RUL":[52,66,119,172],"importance.":[56],"We":[57],"consider":[58],"data-driven":[60],"approaches":[61],"for":[62,120],"diamond-coated":[63,149,174],"estimation":[67],"based":[68,177],"on":[69,178],"AE":[70,96,145,179],"sensor":[71,97,146],"data,":[72,147],"since":[73],"it":[74],"difficult":[76],"construct":[78],"an":[79],"explicit":[80],"mathematical":[81],"degradation":[82,102,135],"model":[83],"seal.":[85],"The":[86,181],"challenges":[87],"this":[89],"work":[90],"are":[91,151],"dealing":[92],"with":[93,104,107],"noisy":[95],"data":[98],"modeling":[100],"fluctuation.":[105],"Faced":[106],"these":[108],"challenges,":[109],"we":[110],"propose":[111],"a":[112],"pipeline":[113],"method":[114,167,184],"CDF-CNN":[115],"estimate":[117,141],"seal:":[122],"WPD-KLD":[123],"raise":[125],"signal-to-noise":[127],"ratio,":[128],"novel":[129],"CDF-based":[130],"statistics":[131],"represent":[133],"CNN":[138],"structure":[139],"RUL.":[142],"To":[143],"acquire":[144],"several":[148],"seals":[150],"tested":[152],"from":[153],"new":[154],"failure":[156],"three":[158],"working":[159],"conditions.":[160],"Experimental":[161],"results":[162],"demonstrate":[163],"that":[164],"proposed":[166,182],"can":[168,185],"accurately":[169],"predict":[170],"signals.":[180],"be":[186],"generalized":[187],"various":[190],"assets.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
