{"id":"https://openalex.org/W7106301736","doi":"https://doi.org/10.1016/j.engappai.2025.113280","title":"Remaining useful life prediction of rotating machine via long short-term memory network with uncertainty quantification","display_name":"Remaining useful life prediction of rotating machine via long short-term memory network with uncertainty quantification","publication_year":2025,"publication_date":"2025-11-21","ids":{"openalex":"https://openalex.org/W7106301736","doi":"https://doi.org/10.1016/j.engappai.2025.113280"},"language":"en","primary_location":{"id":"doi:10.1016/j.engappai.2025.113280","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2025.113280","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.engappai.2025.113280","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jialong He","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jialong He","raw_affiliation_strings":["Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, Jilin, 130022, China","School of Mechanical and Aerospace Engineering, Jilin University, Changchun, Jilin, 130022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, Jilin, 130022, China","institution_ids":[]},{"raw_affiliation_string":"School of Mechanical and Aerospace Engineering, Jilin University, Changchun, Jilin, 130022, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhenbiao Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenbiao Ma","raw_affiliation_strings":["Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, Jilin, 130022, China","School of Mechanical and Aerospace Engineering, Jilin University, Changchun, Jilin, 130022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, Jilin, 130022, China","institution_ids":[]},{"raw_affiliation_string":"School of Mechanical and Aerospace Engineering, Jilin University, Changchun, Jilin, 130022, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yan Liu","orcid":"https://orcid.org/0000-0002-2368-6610"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yan Liu","raw_affiliation_strings":["Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, Jilin, 130022, China","School of Mechanical and Aerospace Engineering, Jilin University, Changchun, Jilin, 130022, China"],"raw_orcid":"https://orcid.org/0000-0002-2368-6610","affiliations":[{"raw_affiliation_string":"Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, Jilin, 130022, China","institution_ids":[]},{"raw_affiliation_string":"School of Mechanical and Aerospace Engineering, Jilin University, Changchun, Jilin, 130022, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhaojun Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaojun Yang","raw_affiliation_strings":["Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, Jilin, 130022, China","School of Mechanical and Aerospace Engineering, Jilin University, Changchun, Jilin, 130022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, Jilin, 130022, China","institution_ids":[]},{"raw_affiliation_string":"School of Mechanical and Aerospace Engineering, Jilin University, Changchun, Jilin, 130022, China","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I194450716"],"apc_list":{"value":3170,"currency":"USD","value_usd":3170},"apc_paid":{"value":3170,"currency":"USD","value_usd":3170},"fwci":5.4452,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.96258911,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"164","issue":null,"first_page":"113280","last_page":"113280"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9779000282287598,"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":0.9779000282287598,"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/T11941","display_name":"Power System Reliability and Maintenance","score":0.0066999997943639755,"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.00559999980032444,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6363999843597412},{"id":"https://openalex.org/keywords/hitting-time","display_name":"Hitting time","score":0.5924999713897705},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5838000178337097},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.5080999732017517},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.4986000061035156},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.48339998722076416},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4417000114917755},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4205999970436096}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7533000111579895},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6363999843597412},{"id":"https://openalex.org/C199277547","wikidata":"https://www.wikidata.org/wiki/Q5872687","display_name":"Hitting time","level":2,"score":0.5924999713897705},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5838000178337097},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.5080999732017517},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.4986000061035156},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.48339998722076416},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4417000114917755},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4205999970436096},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3573000133037567},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3391000032424927},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3138999938964844},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3059999942779541},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.30570000410079956},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.275299996137619},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.2736999988555908},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2712000012397766},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C173291955","wikidata":"https://www.wikidata.org/wiki/Q732332","display_name":"Weibull distribution","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.259799987077713},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.251800000667572},{"id":"https://openalex.org/C137668524","wikidata":"https://www.wikidata.org/wiki/Q189813","display_name":"Censoring (clinical trials)","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.engappai.2025.113280","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2025.113280","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.engappai.2025.113280","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2025.113280","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4371899366378784,"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production"}],"awards":[{"id":"https://openalex.org/G938828115","display_name":null,"funder_award_id":"20240101023JJ","funder_id":"https://openalex.org/F4320310121","funder_display_name":"Natural Science Foundation of Jilin Province"}],"funders":[{"id":"https://openalex.org/F4320310121","display_name":"Natural Science Foundation of Jilin Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1998549657","https://openalex.org/W2001129496","https://openalex.org/W2005523062","https://openalex.org/W2108898839","https://openalex.org/W2904460913","https://openalex.org/W3111012757","https://openalex.org/W3177862163","https://openalex.org/W4281874603","https://openalex.org/W4362009348","https://openalex.org/W4372233714","https://openalex.org/W4377089044","https://openalex.org/W4379618722","https://openalex.org/W4379622050","https://openalex.org/W4381849123","https://openalex.org/W4382119021","https://openalex.org/W4385152143","https://openalex.org/W4385448147","https://openalex.org/W4385929977","https://openalex.org/W4386134686","https://openalex.org/W4386926034","https://openalex.org/W4387686310","https://openalex.org/W4387861048","https://openalex.org/W4388115022","https://openalex.org/W4388793551","https://openalex.org/W4388968784","https://openalex.org/W4389403415","https://openalex.org/W4390770102","https://openalex.org/W4391074247","https://openalex.org/W4391362888","https://openalex.org/W4391744632","https://openalex.org/W4391755707","https://openalex.org/W4392432861","https://openalex.org/W4399878204","https://openalex.org/W4399980616","https://openalex.org/W4399990749","https://openalex.org/W4400182204","https://openalex.org/W4401740167","https://openalex.org/W4402197569","https://openalex.org/W4402474702","https://openalex.org/W4402898796","https://openalex.org/W4404869857","https://openalex.org/W4404996217","https://openalex.org/W4407723216"],"related_works":[],"abstract_inverted_index":{"Remaining":[0],"useful":[1],"life":[2],"(RUL)":[3],"prediction":[4,48,113,188],"of":[5,81,90,104,111,172,181],"rotating":[6],"machinery":[7],"is":[8,74,106,114,143],"critical":[9],"for":[10,98],"intelligent":[11],"maintenance":[12],"and":[13,28,119,129,174,190],"ensuring":[14],"equipment":[15],"reliability.":[16],"However,":[17],"existing":[18,195],"methods":[19],"often":[20],"struggle":[21],"to":[22,30,76,194],"capture":[23],"the":[24,33,36,64,78,82,88,99,109,112,117,130,154,162],"long-term":[25],"degradation":[26,59,83,160],"trends":[27],"fail":[29],"adequately":[31],"quantify":[32],"uncertainty":[34,110],"in":[35,187],"predictions.":[37],"To":[38],"address":[39],"these":[40],"challenges,":[41],"this":[42],"paper":[43],"proposes":[44],"a":[45,52,68,166,175],"novel":[46],"RUL":[47,105],"method":[49,142,164],"based":[50,62,86],"on":[51,63,87,146,153],"long":[53,69],"short-term":[54,70],"memory-Wiener":[55],"process-Bayesian":[56],"optimization":[57,138],"(LSTM-WP-Bo)":[58],"model.":[60],"First,":[61],"Wiener":[65],"process":[66],"(WP),":[67],"memory":[71],"(LSTM)":[72],"network":[73],"used":[75],"model":[77],"drift":[79,118],"function":[80,102],"process.":[84],"Secondly,":[85],"concept":[89],"first":[91],"hitting":[92],"time":[93],"(FHT),":[94],"an":[95],"approximate":[96],"expression":[97],"probability":[100],"density":[101],"(PDF)":[103],"derived,":[107],"while":[108],"quantified.":[115],"Lastly,":[116],"diffusion":[120],"coefficients":[121],"are":[122,134],"estimated":[123],"using":[124],"maximum":[125],"likelihood":[126],"estimation":[127],"(MLE),":[128],"LSTM":[131],"network's":[132],"hyperparameters":[133],"optimized":[135],"through":[136],"Bayesian":[137],"(Bo).":[139],"The":[140],"proposed":[141,163],"analyzed":[144],"comparatively":[145],"three":[147],"datasets.":[148],"For":[149],"example,":[150],"after":[151],"validation":[152],"servo":[155],"turret":[156],"power":[157],"head":[158],"system":[159],"dataset,":[161],"achieves":[165],"root":[167],"mean":[168,176],"square":[169],"error":[170,179],"(RMSE)":[171],"15.55":[173],"absolute":[177],"percentage":[178],"(MAPE)":[180],"12.91":[182],"%,":[183],"demonstrating":[184],"significant":[185],"improvements":[186],"accuracy":[189],"robustness":[191],"when":[192],"compared":[193],"methods.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":7}],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2025-11-23T00:00:00"}