{"id":"https://openalex.org/W4402474702","doi":"https://doi.org/10.1109/tii.2024.3450003","title":"Incremental Contrast Hybrid Model for Online Remaining Useful Life Prediction With Uncertainty Quantification in Machines","display_name":"Incremental Contrast Hybrid Model for Online Remaining Useful Life Prediction With Uncertainty Quantification in Machines","publication_year":2024,"publication_date":"2024-09-12","ids":{"openalex":"https://openalex.org/W4402474702","doi":"https://doi.org/10.1109/tii.2024.3450003"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2024.3450003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3450003","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Industrial Informatics","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/A5091198711","display_name":"Shushuai Xie","orcid":"https://orcid.org/0000-0003-2925-1041"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shushuai Xie","raw_affiliation_strings":["State Key Laboratory of Aerospace Power System and Plasma Technology, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Aerospace Power System and Plasma Technology, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100708496","display_name":"Wei Cheng","orcid":"https://orcid.org/0000-0002-2032-7815"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Cheng","raw_affiliation_strings":["State Key Laboratory of Aerospace Power System and Plasma Technology, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Aerospace Power System and Plasma Technology, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078416176","display_name":"Ji Xing","orcid":"https://orcid.org/0000-0001-6730-9094"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji Xing","raw_affiliation_strings":["China Nuclear Power Engineering Company Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Nuclear Power Engineering Company Ltd., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045353377","display_name":"Zelin Nie","orcid":"https://orcid.org/0000-0003-4760-3581"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zelin Nie","raw_affiliation_strings":["State Key Laboratory of Aerospace Power System and Plasma Technology, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Aerospace Power System and Plasma Technology, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100779843","display_name":"Xuefeng Chen","orcid":"https://orcid.org/0000-0002-0130-3172"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefeng Chen","raw_affiliation_strings":["State Key Laboratory of Aerospace Power System and Plasma Technology, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Aerospace Power System and Plasma Technology, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101461655","display_name":"Lin Gao","orcid":"https://orcid.org/0000-0002-5038-9953"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Gao","raw_affiliation_strings":["State Key Laboratory of Aerospace Power System and Plasma Technology, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Aerospace Power System and Plasma Technology, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026885241","display_name":"Qian Huang","orcid":"https://orcid.org/0000-0002-6205-9900"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian Huang","raw_affiliation_strings":["China Nuclear Power Engineering Company Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Nuclear Power Engineering Company Ltd., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034141964","display_name":"Rongyong Zhang","orcid":"https://orcid.org/0000-0001-8424-5707"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rongyong Zhang","raw_affiliation_strings":["China Nuclear Power Engineering Company Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Nuclear Power Engineering Company Ltd., Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5091198711"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":3.2188,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.92241422,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"20","issue":"12","first_page":"14308","last_page":"14320"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9534000158309937,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9534000158309937,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9458000063896179,"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/T13690","display_name":"Quality and Safety in Healthcare","score":0.9089999794960022,"subfield":{"id":"https://openalex.org/subfields/3607","display_name":"Medical Laboratory Technology"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.658380389213562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5348984003067017},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.4282815158367157},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4184727072715759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38060539960861206},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.338203489780426},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3122350573539734}],"concepts":[{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.658380389213562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5348984003067017},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.4282815158367157},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4184727072715759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38060539960861206},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.338203489780426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3122350573539734},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2024.3450003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3450003","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[{"id":"https://openalex.org/G5889130711","display_name":null,"funder_award_id":"2023-ZDLNY70","funder_id":"https://openalex.org/F4320336565","funder_display_name":"Key Science and Technology Program of Shaanxi Province"}],"funders":[{"id":"https://openalex.org/F4320327721","display_name":"K. C. Wong Education Foundation","ror":null},{"id":"https://openalex.org/F4320328717","display_name":"China National Nuclear Corporation","ror":"https://ror.org/01d5ymp84"},{"id":"https://openalex.org/F4320336565","display_name":"Key Science and Technology Program of Shaanxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1969150846","https://openalex.org/W2108898839","https://openalex.org/W2120841219","https://openalex.org/W2864622186","https://openalex.org/W2901287750","https://openalex.org/W2904460913","https://openalex.org/W2981973403","https://openalex.org/W3033580259","https://openalex.org/W3159184215","https://openalex.org/W3205961258","https://openalex.org/W3212919100","https://openalex.org/W4220708274","https://openalex.org/W4226395004","https://openalex.org/W4226397853","https://openalex.org/W4281874603","https://openalex.org/W4283798331","https://openalex.org/W4285240340","https://openalex.org/W4293370556","https://openalex.org/W4293704741","https://openalex.org/W4307290295","https://openalex.org/W4307734808","https://openalex.org/W4308147715","https://openalex.org/W4311421441","https://openalex.org/W4312456926","https://openalex.org/W4312761066","https://openalex.org/W4312975111","https://openalex.org/W4318017293","https://openalex.org/W4323108654","https://openalex.org/W4323914173","https://openalex.org/W4376286506","https://openalex.org/W4381786373","https://openalex.org/W4382364123","https://openalex.org/W4383617438","https://openalex.org/W4387441449","https://openalex.org/W4387757497","https://openalex.org/W4390874156","https://openalex.org/W4391806580","https://openalex.org/W6736057607","https://openalex.org/W6856526273"],"related_works":["https://openalex.org/W1991093342","https://openalex.org/W2069592018","https://openalex.org/W2075740387","https://openalex.org/W2358990940","https://openalex.org/W2093931120","https://openalex.org/W2078622645","https://openalex.org/W2170798819","https://openalex.org/W2329812990","https://openalex.org/W3127311823","https://openalex.org/W2349116365"],"abstract_inverted_index":{"Real-time":[0],"and":[1,14,124,203,238],"accurate":[2],"prediction":[3,27,41,70,91,141,169,236],"of":[4,18,24,136,164,170,188,192,207,217],"remaining":[5],"useful":[6],"life":[7],"(RUL)":[8],"is":[9,28,51,86,118,130,174,196],"important":[10],"to":[11,30,44,53,65,109,139,221],"safe":[12],"operation":[13],"maintenance":[15],"(O&M)":[16],"planning":[17],"mechanical":[19,113],"equipment.":[20],"However,":[21],"the":[22,40,47,56,81,97,103,145,149,157,171,177,180,184,193,204,208,215,218,234],"uncertainty":[23,93],"online":[25,59,89,121,133,155,162,168,231],"RUL":[26,69,90,173,235],"difficult":[29,43],"predict":[31],"with":[32,92,102],"most":[33],"current":[34],"deep":[35],"learning":[36,99,128],"(DL)-based":[37],"methods,":[38],"making":[39],"results":[42,213],"convince.":[45],"Furthermore,":[46],"offline-trained":[48],"DL":[49],"model":[50,85,182,224],"unable":[52],"adaptively":[54],"update":[55,223],"network":[57,160],"parameters":[58,138,225],"when":[60,226],"acquiring":[61],"new":[62,227],"data,":[63],"leading":[64],"a":[66,116],"decrease":[67],"in":[68,112],"accuracy.":[71],"To":[72],"overcome":[73],"these":[74],"problems,":[75],"an":[76,125],"innovative":[77],"approach":[78],"based":[79],"on":[80],"incremental":[82,126],"contrast":[83],"hybrid":[84,181],"proposed":[87,158,194,219],"for":[88,120,132,161],"quantification,":[94],"which":[95],"combines":[96],"contrastive":[98,127],"transformer":[100],"(CLformer)":[101],"enhanced":[104],"generalized":[105],"Wiener":[106],"process":[107],"(EGWP)":[108],"describe":[110],"trends":[111],"degradation.":[114],"First,":[115],"CLformer":[117,137,159],"developed":[119],"trend":[122],"prediction,":[123],"strategy":[129],"designed":[131],"adaptive":[134],"updating":[135,163],"reduce":[140],"offset":[142],"errors.":[143],"Then,":[144],"degradation":[146],"increments":[147],"within":[148],"EGWP":[150,165],"state-space":[151],"equations":[152],"are":[153,229],"predicted":[154],"by":[156,176],"parameters.":[166],"Finally,":[167],"machine":[172],"provided":[175],"CLformer,":[178],"whereas":[179],"provides":[183],"probability":[185],"density":[186],"function":[187],"RUL.":[189],"The":[190,212],"effectiveness":[191],"method":[195,220],"verified":[197],"using":[198],"two":[199],"publicly":[200],"available":[201],"datasets":[202],"journal-bearing":[205],"dataset":[206],"nuclear-circulating":[209],"water":[210],"pump.":[211],"demonstrate":[214],"ability":[216],"dynamically":[222],"data":[228],"acquired":[230],"while":[232],"giving":[233],"values":[237],"uncertainties.":[239]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}