{"id":"https://openalex.org/W3115104792","doi":"https://doi.org/10.1109/access.2020.3047928","title":"A Data-Driven Maintenance Framework Under Imperfect Inspections for Deteriorating Systems Using Multitask Learning-Based Status Prognostics","display_name":"A Data-Driven Maintenance Framework Under Imperfect Inspections for Deteriorating Systems Using Multitask Learning-Based Status Prognostics","publication_year":2020,"publication_date":"2020-12-29","ids":{"openalex":"https://openalex.org/W3115104792","doi":"https://doi.org/10.1109/access.2020.3047928","mag":"3115104792"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3047928","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3047928","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09310204.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09310204.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100715086","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-5665-3137"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5665-3137","affiliations":[{"raw_affiliation_string":"Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100461792","display_name":"Jianguo Zhang","orcid":"https://orcid.org/0000-0002-5926-1294"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianguo Zhang","raw_affiliation_strings":["Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":{"value":1750,"currency":"USD","value_usd":1750},"apc_paid":{"value":1750,"currency":"USD","value_usd":1750},"fwci":1.7042,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.82664375,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"9","issue":null,"first_page":"3616","last_page":"3629"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9968000054359436,"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"}},"topics":[{"id":"https://openalex.org/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9968000054359436,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9959999918937683,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9805999994277954,"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/prognostics","display_name":"Prognostics","score":0.9400517344474792},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7604041695594788},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6949689984321594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5557055473327637},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5494135022163391},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5166543126106262},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.5119117498397827},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.49837207794189453},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4959491193294525},{"id":"https://openalex.org/keywords/maintenance-engineering","display_name":"Maintenance engineering","score":0.4676463305950165},{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"Condition monitoring","score":0.4424506425857544},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4332827925682068},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43008026480674744},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3446415960788727},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1622113287448883}],"concepts":[{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.9400517344474792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7604041695594788},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6949689984321594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5557055473327637},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5494135022163391},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5166543126106262},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.5119117498397827},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.49837207794189453},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4959491193294525},{"id":"https://openalex.org/C23725684","wikidata":"https://www.wikidata.org/wiki/Q616377","display_name":"Maintenance engineering","level":2,"score":0.4676463305950165},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.4424506425857544},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4332827925682068},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43008026480674744},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3446415960788727},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1622113287448883},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"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":2,"locations":[{"id":"doi:10.1109/access.2020.3047928","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3047928","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09310204.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e31535963c2d4af8871ca567de1814ac","is_oa":true,"landing_page_url":"https://doaj.org/article/e31535963c2d4af8871ca567de1814ac","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 3616-3629 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3047928","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3047928","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09310204.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3570956670","display_name":null,"funder_award_id":"51675026","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":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3115104792.pdf","grobid_xml":"https://content.openalex.org/works/W3115104792.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1494192115","https://openalex.org/W1495049647","https://openalex.org/W1522301498","https://openalex.org/W1536680647","https://openalex.org/W1974364410","https://openalex.org/W2002728105","https://openalex.org/W2064062935","https://openalex.org/W2064675550","https://openalex.org/W2095278535","https://openalex.org/W2120841219","https://openalex.org/W2140309668","https://openalex.org/W2310466376","https://openalex.org/W2605516844","https://openalex.org/W2609597778","https://openalex.org/W2738563279","https://openalex.org/W2753709519","https://openalex.org/W2781862948","https://openalex.org/W2787606231","https://openalex.org/W2913340405","https://openalex.org/W2920083100","https://openalex.org/W2952947910","https://openalex.org/W2953144469","https://openalex.org/W2975677389","https://openalex.org/W2981386789","https://openalex.org/W2983948788","https://openalex.org/W2987147016","https://openalex.org/W2997869253","https://openalex.org/W3004893834","https://openalex.org/W3007600452","https://openalex.org/W3009832084","https://openalex.org/W3015173390","https://openalex.org/W3015211490","https://openalex.org/W3021311111","https://openalex.org/W3026432090","https://openalex.org/W3081642530","https://openalex.org/W6631190155","https://openalex.org/W6747371815","https://openalex.org/W6748281098"],"related_works":["https://openalex.org/W2908973203","https://openalex.org/W2801712269","https://openalex.org/W1872896676","https://openalex.org/W2156691445","https://openalex.org/W2045186954","https://openalex.org/W3000986292","https://openalex.org/W1502469213","https://openalex.org/W2568310397","https://openalex.org/W2123638926","https://openalex.org/W2586143229"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,28,53,57,62,68,125],"data-driven,":[4],"condition-based":[5],"maintenance":[6,38,139,151,195],"framework":[7,175],"(DCBM)":[8],"for":[9,150],"deteriorating":[10],"equipment":[11,47],"under":[12],"the":[13,46,85,111,116,135,138,148,159,162,166,172,179,193],"impact":[14],"of":[15,43,56,121,137,147,161,171,181],"varying":[16],"environments":[17],"and":[18,30,37,88,97,186],"natural":[19],"aging.":[20],"The":[21,101,169],"equipment's":[22],"degradation":[23,48,96,184],"status":[24],"is":[25,143,176,189],"determined":[26],"by":[27,178],"prognostic":[29],"health":[31],"monitoring":[32,35,86],"method.":[33],"Generally,":[34],"data":[36],"inspections":[39,156],"are":[40],"imperfect":[41,155],"because":[42],"uncertainties":[44,163],"in":[45,165],"process,":[49],"which":[50,114],"may":[51],"prevent":[52],"reliable":[54],"evaluation":[55],"system's":[58],"deterioration.":[59],"By":[60],"utilizing":[61],"deep":[63,130],"learning":[64,78,105,132],"technique,":[65],"we":[66,127],"construct":[67],"new":[69],"stacked":[70],"autoencoder":[71],"long":[72],"short-term":[73],"memory":[74],"(SAE-LSTM)":[75],"network-based":[76],"multitask":[77,104,131],"model":[79,133,188],"to":[80,93,110,157],"extract":[81],"state":[82],"features":[83],"from":[84],"data,":[87],"then":[89],"perform":[90],"multistep":[91],"forecasting":[92,142],"obtain":[94],"performance":[95],"failure":[98],"probability":[99],"information.":[100],"developed":[102],"SAE-LSTM-based":[103],"achieves":[106],"prognosis":[107],"results":[108],"close":[109],"actual":[112],"values,":[113],"indicates":[115],"excellent":[117],"feature":[118],"extraction":[119],"capability":[120],"this":[122,129,187],"model.":[123],"As":[124],"result,":[126],"introduce":[128],"into":[134],"optimization":[136],"process.":[140],"Probabilistic":[141],"used":[144],"as":[145],"one":[146],"criteria":[149],"decisions":[152],"made":[153],"with":[154],"address":[158],"influence":[160],"involved":[164],"prognoses":[167],"results.":[168],"effectiveness":[170],"proposed":[173],"DCBM":[174],"illustrated":[177],"application":[180],"an":[182],"engine":[183],"dataset,":[185],"more":[190],"cost-effective":[191],"than":[192],"baseline":[194],"policies.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}