{"id":"https://openalex.org/W4415399123","doi":"https://doi.org/10.1109/tr.2025.3619424","title":"Uncertainty NVAE-SVDD Based on Monte Carlo Dropout for Trustworthy Detection of Mechanical Failures","display_name":"Uncertainty NVAE-SVDD Based on Monte Carlo Dropout for Trustworthy Detection of Mechanical Failures","publication_year":2025,"publication_date":"2025-10-21","ids":{"openalex":"https://openalex.org/W4415399123","doi":"https://doi.org/10.1109/tr.2025.3619424"},"language":null,"primary_location":{"id":"doi:10.1109/tr.2025.3619424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2025.3619424","pdf_url":null,"source":{"id":"https://openalex.org/S87725633","display_name":"IEEE Transactions on Reliability","issn_l":"0018-9529","issn":["0018-9529","1558-1721"],"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 Reliability","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/A5100334000","display_name":"Zhiyi He","orcid":"https://orcid.org/0000-0002-1334-8677"},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiyi He","raw_affiliation_strings":["College of Mechanical and Vehicle Engineering, Changsha University of Science and Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Vehicle Engineering, Changsha University of Science and Technology, Changsha, China","institution_ids":["https://openalex.org/I56934997"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010128384","display_name":"Qing Liu","orcid":"https://orcid.org/0000-0002-5797-8179"},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Liu","raw_affiliation_strings":["College of Mechanical and Vehicle Engineering, Changsha University of Science and Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Vehicle Engineering, Changsha University of Science and Technology, Changsha, China","institution_ids":["https://openalex.org/I56934997"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044361588","display_name":"Haidong Shao","orcid":"https://orcid.org/0000-0001-7106-0009"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haidong Shao","raw_affiliation_strings":["College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bin Yang","orcid":"https://orcid.org/0009-0004-2906-2560"},"institutions":[{"id":"https://openalex.org/I4210126257","display_name":"CRRC (China)","ror":"https://ror.org/033g21894","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210126257"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Yang","raw_affiliation_strings":["CRRC Zhuzhou Institute Company Ltd., Zhuzhou, China"],"affiliations":[{"raw_affiliation_string":"CRRC Zhuzhou Institute Company Ltd., Zhuzhou, China","institution_ids":["https://openalex.org/I4210126257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042310292","display_name":"Ming Zeng","orcid":"https://orcid.org/0000-0003-0233-6918"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zeng","raw_affiliation_strings":["School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100334000"],"corresponding_institution_ids":["https://openalex.org/I56934997"],"apc_list":null,"apc_paid":null,"fwci":4.6468,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.95208206,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"74","issue":"4","first_page":"5544","last_page":"5553"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9693999886512756,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9693999886512756,"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/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.6395999789237976},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.609000027179718},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5412999987602234},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5270000100135803},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4779999852180481},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.45980000495910645},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4523000121116638},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4327999949455261},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4230000078678131}],"concepts":[{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.6395999789237976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6380000114440918},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.609000027179718},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5412999987602234},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5270000100135803},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5214999914169312},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4779999852180481},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.45980000495910645},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4523000121116638},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4327999949455261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.423799991607666},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4230000078678131},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3779999911785126},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.3767000138759613},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36980000138282776},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.3628999888896942},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.32269999384880066},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.2978000044822693},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.29760000109672546},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tr.2025.3619424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2025.3619424","pdf_url":null,"source":{"id":"https://openalex.org/S87725633","display_name":"IEEE Transactions on Reliability","issn_l":"0018-9529","issn":["0018-9529","1558-1721"],"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 Reliability","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4970459435","display_name":null,"funder_award_id":"52305091","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2997377600","https://openalex.org/W3043609702","https://openalex.org/W3159922383","https://openalex.org/W3170022067","https://openalex.org/W3195533526","https://openalex.org/W3196420684","https://openalex.org/W3200904534","https://openalex.org/W3210805939","https://openalex.org/W4210680043","https://openalex.org/W4229452267","https://openalex.org/W4287844218","https://openalex.org/W4295939758","https://openalex.org/W4302028121","https://openalex.org/W4307903596","https://openalex.org/W4311807066","https://openalex.org/W4312644849","https://openalex.org/W4365398010","https://openalex.org/W4382280213","https://openalex.org/W4386917897","https://openalex.org/W4387757571","https://openalex.org/W4388878371","https://openalex.org/W4389068150","https://openalex.org/W4391128477","https://openalex.org/W4391646673","https://openalex.org/W4391947957","https://openalex.org/W4394627257","https://openalex.org/W4394744485","https://openalex.org/W4394966841","https://openalex.org/W4400202631","https://openalex.org/W4406411288","https://openalex.org/W4406935929","https://openalex.org/W4408917557","https://openalex.org/W4409418923","https://openalex.org/W4410239913","https://openalex.org/W4410738129","https://openalex.org/W4411473296"],"related_works":[],"abstract_inverted_index":{"Most":[0],"mechanical":[1,46],"fault":[2,47,121,165],"detection":[3,35,48,166],"methods":[4],"rely":[5],"on":[6,51],"deterministic":[7],"feature":[8,83],"extraction":[9],"and":[10,142,156,161],"fail":[11],"to":[12,18,106,138],"model":[13],"prediction":[14,100],"uncertainty,":[15],"often":[16],"leading":[17],"overconfident":[19],"errors":[20],"when":[21],"facing":[22],"unknown":[23,143],"or":[24],"borderline":[25],"faults":[26],"in":[27,114,159],"complex":[28],"conditions.":[29],"This":[30],"compromises":[31],"the":[32,60,82,88,99,115,149],"reliability":[33],"of":[34,96],"outcomes.":[36],"To":[37],"address":[38],"these":[39],"issues,":[40],"this":[41],"article":[42],"proposes":[43],"a":[44,73,76,108],"trustworthy":[45],"method":[49,71,125,151],"based":[50],"uncertainty":[52,97,137],"modeling":[53],"using":[54],"Monte":[55],"Carlo":[56],"(MC)":[57],"dropout":[58,90],"within":[59],"nouveau":[61],"variational":[62],"autoencoder":[63],"support":[64],"vector":[65],"data":[66],"description":[67],"(NVAE-SVDD)":[68],"framework.":[69],"The":[70,123],"employs":[72],"NVAE":[74,116],"with":[75],"hierarchical":[77],"latent":[78,117],"variable":[79],"structure":[80],"as":[81],"extractor.":[84],"By":[85],"explicitly":[86],"incorporating":[87],"MC":[89],"strategy,":[91],"it":[92],"enables":[93],"effective":[94],"quantification":[95],"during":[98],"process.":[101],"Meanwhile,":[102],"SVDD":[103],"is":[104],"used":[105],"construct":[107],"compact":[109],"boundary":[110,140],"around":[111],"normal":[112,130],"samples":[113],"space,":[118],"enabling":[119],"efficient":[120],"identification.":[122],"proposed":[124,150],"not":[126],"only":[127],"accurately":[128],"identifies":[129],"conditions":[131],"but":[132],"also":[133],"fully":[134],"leverages":[135],"predictive":[136],"distinguish":[139],"anomalies":[141],"faults.":[144],"Experimental":[145],"results":[146],"show":[147],"that":[148],"outperforms":[152],"traditional":[153],"one-class":[154],"models":[155],"uncertainty-free":[157],"baselines":[158],"accuracy":[160],"robustness,":[162],"greatly":[163],"improving":[164],"reliability.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-22T00:00:00"}