{"id":"https://openalex.org/W3158911546","doi":"https://doi.org/10.1109/access.2021.3077192","title":"Long Short-Term Memory Networks for Facility Infrastructure Failure and Remaining Useful Life Prediction","display_name":"Long Short-Term Memory Networks for Facility Infrastructure Failure and Remaining Useful Life Prediction","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3158911546","doi":"https://doi.org/10.1109/access.2021.3077192","mag":"3158911546"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3077192","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3077192","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09420660.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/ielx7/6287639/9312710/09420660.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017628176","display_name":"Rodney Kizito","orcid":"https://orcid.org/0000-0002-0890-128X"},"institutions":[{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rodney Kizito","raw_affiliation_strings":["The University of Tennessee, Knoxville, TN, USA"],"raw_orcid":"https://orcid.org/0000-0002-0890-128X","affiliations":[{"raw_affiliation_string":"The University of Tennessee, Knoxville, TN, USA","institution_ids":["https://openalex.org/I75027704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069393170","display_name":"Phillip Scruggs","orcid":"https://orcid.org/0000-0001-7720-1263"},"institutions":[{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Phillip Scruggs","raw_affiliation_strings":["The University of Tennessee, Knoxville, TN, USA"],"raw_orcid":"https://orcid.org/0000-0001-7720-1263","affiliations":[{"raw_affiliation_string":"The University of Tennessee, Knoxville, TN, USA","institution_ids":["https://openalex.org/I75027704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100406401","display_name":"Xueping Li","orcid":"https://orcid.org/0000-0003-1990-0159"},"institutions":[{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xueping Li","raw_affiliation_strings":["The University of Tennessee, Knoxville, TN, USA"],"raw_orcid":"https://orcid.org/0000-0003-1990-0159","affiliations":[{"raw_affiliation_string":"The University of Tennessee, Knoxville, TN, USA","institution_ids":["https://openalex.org/I75027704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102974993","display_name":"Michael DeVinney","orcid":"https://orcid.org/0000-0003-1919-2754"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Devinney","raw_affiliation_strings":["Consolidated Nuclear Security, LLC, Oak Ridge, TN, USA"],"raw_orcid":"https://orcid.org/0000-0003-1919-2754","affiliations":[{"raw_affiliation_string":"Consolidated Nuclear Security, LLC, Oak Ridge, TN, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050315692","display_name":"Joseph Jansen","orcid":"https://orcid.org/0000-0002-3790-5124"},"institutions":[{"id":"https://openalex.org/I1335486098","display_name":"Electric Power Research Institute","ror":"https://ror.org/02dqztz06","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1335486098"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph Jansen","raw_affiliation_strings":["Electric Power Research Institute, Oak Ridge, TN, USA"],"raw_orcid":"https://orcid.org/0000-0002-3790-5124","affiliations":[{"raw_affiliation_string":"Electric Power Research Institute, Oak Ridge, TN, USA","institution_ids":["https://openalex.org/I1335486098"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050062951","display_name":"R.L. Kress","orcid":"https://orcid.org/0000-0002-4431-0401"},"institutions":[{"id":"https://openalex.org/I1335486098","display_name":"Electric Power Research Institute","ror":"https://ror.org/02dqztz06","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1335486098"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Reid Kress","raw_affiliation_strings":["Electric Power Research Institute, Oak Ridge, TN, USA"],"raw_orcid":"https://orcid.org/0000-0002-4431-0401","affiliations":[{"raw_affiliation_string":"Electric Power Research Institute, Oak Ridge, TN, USA","institution_ids":["https://openalex.org/I1335486098"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5017628176"],"corresponding_institution_ids":["https://openalex.org/I75027704"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.5265,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.82081335,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"67585","last_page":"67594"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9944999814033508,"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"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.975600004196167,"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/computer-science","display_name":"Computer science","score":0.7621053457260132},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5593532919883728},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.5372341275215149},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5121300220489502},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.49607428908348083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47760769724845886},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4720666706562042},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4585414528846741},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4556288421154022},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4527837932109833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38149115443229675}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7621053457260132},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5593532919883728},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.5372341275215149},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5121300220489502},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.49607428908348083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47760769724845886},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4720666706562042},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4585414528846741},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4556288421154022},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4527837932109833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38149115443229675},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3077192","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3077192","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09420660.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:dc379b51be2345f584f97bf2d603cf0e","is_oa":true,"landing_page_url":"https://doaj.org/article/dc379b51be2345f584f97bf2d603cf0e","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 67585-67594 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3077192","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3077192","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09420660.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":[{"score":0.46000000834465027,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3158911546.pdf","grobid_xml":"https://content.openalex.org/works/W3158911546.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W243674440","https://openalex.org/W273955616","https://openalex.org/W1966793308","https://openalex.org/W1974586865","https://openalex.org/W1999393241","https://openalex.org/W2029959080","https://openalex.org/W2033800551","https://openalex.org/W2064675550","https://openalex.org/W2118023920","https://openalex.org/W2136848157","https://openalex.org/W2401694825","https://openalex.org/W2603304445","https://openalex.org/W2724573302","https://openalex.org/W2765858647","https://openalex.org/W2767634046","https://openalex.org/W2783365435","https://openalex.org/W2794330891","https://openalex.org/W2797405679","https://openalex.org/W2810057162","https://openalex.org/W2897557170","https://openalex.org/W2944342107","https://openalex.org/W2966675498","https://openalex.org/W3013120195","https://openalex.org/W3162355067","https://openalex.org/W4242121546","https://openalex.org/W6610017368","https://openalex.org/W6643840107","https://openalex.org/W6745339876","https://openalex.org/W6796020316"],"related_works":["https://openalex.org/W2912153778","https://openalex.org/W4387163678","https://openalex.org/W4288108708","https://openalex.org/W2973430807","https://openalex.org/W4385280324","https://openalex.org/W2984436043","https://openalex.org/W4390245176","https://openalex.org/W2912831041","https://openalex.org/W2890685186","https://openalex.org/W3173606726"],"abstract_inverted_index":{"Sensors":[0],"attached":[1,143],"to":[2,17,22,69,81,103,144,161,200],"an":[3,140],"asset":[4],"acquiring":[5,135],"vibration":[6],"patterns":[7],"during":[8],"both":[9],"operational":[10],"and":[11,21,51,97,114,176,192,212],"failure":[12,49,86,113,119,190,210],"states":[13],"have":[14],"been":[15],"used":[16,80],"diagnose":[18],"fault":[19],"conditions":[20],"predict":[23,82],"future":[24],"failures":[25],"of":[26,43,57,85,111,118,151,163,187],"the":[27,83,109,116,132,152,156,164,182,195,201,204,214],"components":[28],"being":[29],"monitored.":[30],"In":[31,92],"this":[32,93],"research,":[33],"we":[34,95],"investigate":[35],"Long":[36],"Short-Term":[37],"Memory":[38],"(LSTM)":[39],"networks,":[40],"a":[41,88,99,104,121,145],"type":[42],"Recurrent":[44],"Neural":[45],"Network":[46],"(RNN),":[47],"for":[48,72,108,174],"diagnosis":[50],"remaining":[52],"useful":[53],"life":[54],"(RUL)":[55],"prognosis":[56],"such":[58],"deteriorating":[59],"components.":[60],"LSTM":[61,101,153,183,205],"networks'":[62],"long-term":[63],"dependency":[64],"capability,":[65],"which":[66],"allows":[67],"LSTM's":[68],"recall":[70],"information":[71],"long":[73],"term":[74],"sequence":[75],"lengths,":[76],"can":[77],"also":[78],"be":[79],"probability":[84,117,191],"within":[87,120],"specified":[89,122],"time":[90,123],"frame.":[91],"paper,":[94],"develop":[96],"apply":[98],"stylized":[100],"model":[102,154],"motor":[105,142,188],"degradation":[106],"dataset":[107,133,158],"purposes":[110],"diagnosing":[112],"predicting":[115,128],"frame,":[124],"as":[125,127,169],"well":[126,208],"RUL.":[129],"We":[130],"developed":[131,157,196],"by":[134],"automated":[136],"sensor":[137],"measurements":[138],"from":[139],"induction":[141],"destructive":[146],"test":[147],"platform.":[148],"The":[149,178],"performance":[150],"on":[155,194],"is":[159,171],"compared":[160,199],"that":[162,181],"Random":[165],"Forest":[166],"(RF)":[167],"algorithm":[168],"RF":[170,202,215],"reputably":[172],"known":[173],"classification":[175,211],"regression.":[177],"results":[179],"demonstrate":[180],"provides":[184],"quality":[185],"predictions":[186],"failure,":[189],"RUL":[193,217],"dataset.":[197],"When":[198],"approach,":[203],"performs":[206],"comparably":[207],"in":[209,216],"outperforms":[213],"prediction.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}