{"id":"https://openalex.org/W7131436802","doi":"https://doi.org/10.1109/tr.2026.3667664","title":"Zero Forgetting Lifelong Dictionary Learning Based on Low-Rank Decomposition for Multimode Process Monitoring","display_name":"Zero Forgetting Lifelong Dictionary Learning Based on Low-Rank Decomposition for Multimode Process Monitoring","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7131436802","doi":"https://doi.org/10.1109/tr.2026.3667664"},"language":null,"primary_location":{"id":"doi:10.1109/tr.2026.3667664","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2026.3667664","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/A5082518323","display_name":"Keke Huang","orcid":"https://orcid.org/0000-0003-3553-3424"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keke Huang","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-3553-3424","affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhongyu Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyu Zhang","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126833684","display_name":"Zixuan Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixuan Chen","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122867897","display_name":"Dehao Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dehao Wu","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-0649-1085","affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126819740","display_name":"Chunhua Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhua Yang","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-3770-9887","affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126839651","display_name":"Weihua Gui","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Gui","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-5337-6445","affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139660479"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24493847,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"75","issue":null,"first_page":"1198","last_page":"1210"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.5491999983787537,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.5491999983787537,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T12676","display_name":"Machine Learning and ELM","score":0.06430000066757202,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.06369999796152115,"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/forgetting","display_name":"Forgetting","score":0.8510000109672546},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5722000002861023},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5485000014305115},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.5034000277519226},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41339999437332153},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.39430001378059387},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.3887999951839447},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.36629998683929443},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.3546999990940094}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.8510000109672546},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6721000075340271},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5722000002861023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5496000051498413},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5485000014305115},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.5034000277519226},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41339999437332153},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.39430001378059387},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.3887999951839447},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3806000053882599},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.36629998683929443},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.3546999990940094},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.3488999903202057},{"id":"https://openalex.org/C5917680","wikidata":"https://www.wikidata.org/wiki/Q2621825","display_name":"Basis function","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3133000135421753},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.30090001225471497},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2865999937057495},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C103275481","wikidata":"https://www.wikidata.org/wiki/Q6787889","display_name":"Matrix representation","level":3,"score":0.2786000072956085},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27570000290870667},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C101645829","wikidata":"https://www.wikidata.org/wiki/Q1781857","display_name":"Multi-mode optical fiber","level":3,"score":0.27079999446868896},{"id":"https://openalex.org/C108771440","wikidata":"https://www.wikidata.org/wiki/Q368475","display_name":"Lifelong learning","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.25769999623298645}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tr.2026.3667664","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2026.3667664","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":[{"id":"https://metadata.un.org/sdg/8","score":0.4827096164226532,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G1168836851","display_name":null,"funder_award_id":"62573440","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4523845054","display_name":null,"funder_award_id":"92467107","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modern":[0],"industrial":[1],"systems":[2],"typically":[3],"operate":[4],"in":[5,13,42,136],"a":[6,39,51,74,86,100,124,146,150,180],"multimode":[7,95],"environment":[8],"due":[9],"to":[10,25,35,68,132,173,230,268],"continuous":[11],"changes":[12],"raw":[14],"materials":[15],"and":[16,38,120,166,287,308],"production":[17],"schedules.":[18],"Traditional":[19],"static":[20],"monitoring":[21,43,311],"methods":[22],"often":[23,54],"struggle":[24],"accurately":[26,160],"capture":[27,161],"the":[28,46,61,66,154,162,168,175,210,226,231,240,248,262,274,280,296],"intricate":[29],"relationships":[30],"between":[31],"different":[32,269],"modes,":[33,179,209,270],"leading":[34],"model":[36,56,67],"mismatches":[37],"significant":[40],"decline":[41],"performance.":[44,312],"On":[45],"other":[47],"hand,":[48],"emergence":[49,176],"of":[50,115,177,220,242,264],"new":[52,62,119,178,201,214,232],"mode":[53,202,233,285],"prompts":[55],"updates":[57],"that":[58,277,295],"focus":[59],"on":[60,187],"data,":[63],"potentially":[64],"causing":[65],"forget":[69],"historical":[70,121,208,221],"knowledge,":[71],"which":[72,158],"is":[73,129,192,258],"phenomenon":[75],"known":[76],"as":[77,153],"catastrophic":[78],"forgetting.":[79],"To":[80],"address":[81,133,174],"these":[82],"issues,":[83],"we":[84],"propose":[85],"zero":[87,181,218],"forgetting":[88,182,219],"lifelong":[89],"dictionary":[90,211],"learning":[91,184,250,306],"(ZFLDL)":[92],"method":[93,128,144,298],"for":[94,199],"process":[96,289,310],"monitoring.":[97,290],"ZFLDL":[98],"integrates":[99],"low-rank":[101,126,147,188],"basis":[102,109,189,197,227,255,266,275],"matrix":[103,110,190,256,267],"growth":[104,191],"mechanism":[105],"with":[106,139,207],"an":[107,140,253],"adaptive":[108,254],"selector,":[111],"enabling":[112],"effective":[113],"representation":[114,138,156,170],"knowledge":[116,215],"across":[117],"both":[118],"modes.":[122],"Specifically,":[123],"novel":[125],"decomposition":[127],"first":[130],"proposed":[131,297],"feature":[134],"redundancy":[135],"data":[137,164],"overcomplete":[141],"dictionary.":[142],"This":[143],"utilizes":[145],"matrix,":[148],"i.e.":[149],"\u201cbasis":[151],"matrix\u201d,":[152],"fundamental":[155],"unit,":[157],"can":[159],"core":[163],"features":[165],"enhance":[167],"dictionary's":[169],"capability.":[171],"Then,":[172],"continual":[183,305],"framework":[185],"based":[186],"proposed.":[193,259],"By":[194,260],"adaptively":[195],"adding":[196],"matrices":[198,228,276],"each":[200,265],"while":[203,216],"freezing":[204],"those":[205],"associated":[206],"efficiently":[212],"assimilates":[213],"ensuring":[217,283],"knowledge.":[222],"Additionally,":[223],"since":[224],"only":[225],"related":[229],"are":[234],"updated,":[235],"this":[236],"approach":[237],"significantly":[238],"reduces":[239],"number":[241],"parameters":[243],"requiring":[244],"training,":[245],"thus":[246],"enhancing":[247],"model's":[249],"efficiency.":[251],"Finally,":[252],"selector":[257],"evaluating":[261],"contribution":[263],"it":[271],"dynamically":[272],"selects":[273],"best":[278],"match":[279],"specific":[281],"mode,":[282],"accurate":[284],"recognition":[286],"reliable":[288],"Extensive":[291],"experiments":[292],"have":[293],"demonstrated":[294],"outperforms":[299],"several":[300],"state-of-the-art":[301],"methods,":[302],"exhibiting":[303],"superior":[304],"capability":[307],"enhanced":[309]},"counts_by_year":[],"updated_date":"2026-03-14T06:41:57.775601","created_date":"2026-02-26T00:00:00"}
