{"id":"https://openalex.org/W2985646419","doi":"https://doi.org/10.23919/iconac.2019.8895037","title":"A condition monitoring method of wind turbines based on Long Short-Term Memory neural network","display_name":"A condition monitoring method of wind turbines based on Long Short-Term Memory neural network","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2985646419","doi":"https://doi.org/10.23919/iconac.2019.8895037","mag":"2985646419"},"language":"en","primary_location":{"id":"doi:10.23919/iconac.2019.8895037","is_oa":false,"landing_page_url":"https://doi.org/10.23919/iconac.2019.8895037","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 25th International Conference on Automation and Computing (ICAC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5014911568","display_name":"Bo Feng","orcid":"https://orcid.org/0000-0003-0382-1456"},"institutions":[{"id":"https://openalex.org/I31847773","display_name":"Zhejiang Ocean University","ror":"https://ror.org/03mys6533","country_code":"CN","type":"education","lineage":["https://openalex.org/I31847773"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Feng","raw_affiliation_strings":["Zhejiang University,Ocean College,Hangzhou,China,310058","Ocean College, Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,Ocean College,Hangzhou,China,310058","institution_ids":["https://openalex.org/I31847773"]},{"raw_affiliation_string":"Ocean College, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I31847773","https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075104676","display_name":"Dahai Zhang","orcid":"https://orcid.org/0000-0002-5708-2196"},"institutions":[{"id":"https://openalex.org/I31847773","display_name":"Zhejiang Ocean University","ror":"https://ror.org/03mys6533","country_code":"CN","type":"education","lineage":["https://openalex.org/I31847773"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dahai Zhang","raw_affiliation_strings":["Zhejiang University,Ocean College,Hangzhou,China,310058","Ocean College, Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,Ocean College,Hangzhou,China,310058","institution_ids":["https://openalex.org/I31847773"]},{"raw_affiliation_string":"Ocean College, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I31847773","https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031841011","display_name":"Yulin Si","orcid":"https://orcid.org/0000-0002-7364-1293"},"institutions":[{"id":"https://openalex.org/I31847773","display_name":"Zhejiang Ocean University","ror":"https://ror.org/03mys6533","country_code":"CN","type":"education","lineage":["https://openalex.org/I31847773"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulin Si","raw_affiliation_strings":["Zhejiang University,Ocean College,Hangzhou,China,310058","Ocean College, Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,Ocean College,Hangzhou,China,310058","institution_ids":["https://openalex.org/I31847773"]},{"raw_affiliation_string":"Ocean College, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I31847773","https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025602255","display_name":"Xiange Tian","orcid":"https://orcid.org/0000-0003-3448-3509"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xiange Tian","raw_affiliation_strings":["Brunel University,Department of Mechanical, Aerospace and Civil Engineering,London,UK,UB8 3PH","Department of Mechanical, Aerospace and Civil Engineering, Brunel University, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brunel University,Department of Mechanical, Aerospace and Civil Engineering,London,UK,UB8 3PH","institution_ids":["https://openalex.org/I59433898"]},{"raw_affiliation_string":"Department of Mechanical, Aerospace and Civil Engineering, Brunel University, London, UK","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046828748","display_name":"Peng Qian","orcid":"https://orcid.org/0000-0002-8263-1927"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Peng Qian","raw_affiliation_strings":["Brunel University,Department of Mechanical, Aerospace and Civil Engineering,London,UK,UB8 3PH","Department of Mechanical, Aerospace and Civil Engineering, Brunel University, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brunel University,Department of Mechanical, Aerospace and Civil Engineering,London,UK,UB8 3PH","institution_ids":["https://openalex.org/I59433898"]},{"raw_affiliation_string":"Department of Mechanical, Aerospace and Civil Engineering, Brunel University, London, UK","institution_ids":["https://openalex.org/I59433898"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9991999864578247,"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":0.9991999864578247,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.9905999898910522,"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/scada","display_name":"SCADA","score":0.9248437881469727},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.7583571672439575},{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"Condition monitoring","score":0.7177181839942932},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6899536848068237},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6880632638931274},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6851982474327087},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5805866122245789},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.48567211627960205},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4849560260772705},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.4772596061229706},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.46275803446769714},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.45447808504104614},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.4362720847129822},{"id":"https://openalex.org/keywords/turbine","display_name":"Turbine","score":0.4339072108268738},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4144511818885803},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36292245984077454},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35731804370880127},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.2827221155166626},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21582216024398804},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.15543591976165771},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09306541085243225}],"concepts":[{"id":"https://openalex.org/C113863187","wikidata":"https://www.wikidata.org/wiki/Q17498","display_name":"SCADA","level":2,"score":0.9248437881469727},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.7583571672439575},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.7177181839942932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6899536848068237},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6880632638931274},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6851982474327087},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5805866122245789},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.48567211627960205},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4849560260772705},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.4772596061229706},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.46275803446769714},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.45447808504104614},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.4362720847129822},{"id":"https://openalex.org/C2778449969","wikidata":"https://www.wikidata.org/wiki/Q130760","display_name":"Turbine","level":2,"score":0.4339072108268738},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4144511818885803},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36292245984077454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35731804370880127},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2827221155166626},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21582216024398804},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.15543591976165771},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09306541085243225},{"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/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/iconac.2019.8895037","is_oa":false,"landing_page_url":"https://doi.org/10.23919/iconac.2019.8895037","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 25th International Conference on Automation and Computing (ICAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1981064558","https://openalex.org/W2039442724","https://openalex.org/W2058931725","https://openalex.org/W2076863095","https://openalex.org/W2078597094","https://openalex.org/W2598141788","https://openalex.org/W2762853480","https://openalex.org/W2883583014","https://openalex.org/W2889165715","https://openalex.org/W2895995371"],"related_works":["https://openalex.org/W2615977515","https://openalex.org/W2115760278","https://openalex.org/W2146396794","https://openalex.org/W2807864071","https://openalex.org/W2809162650","https://openalex.org/W2388279172","https://openalex.org/W2799162308","https://openalex.org/W2741863531","https://openalex.org/W2523553285","https://openalex.org/W1969365005"],"abstract_inverted_index":{"A":[0],"reliable":[1],"condition":[2,47,62,120],"monitoring":[3,17,48,63],"system":[4],"can":[5,50,83,115],"help":[6],"improve":[7],"the":[8,39,85,88,92,101,109,125,131],"reliability":[9],"of":[10,41,77,124],"wind":[11,66],"turbines":[12,67],"and":[13,23,91,108],"reduce":[14],"cost.":[15],"Condition":[16],"method":[18,33,64,127],"based":[19,68],"on":[20,69],"supervisory":[21],"control":[22],"data":[24,27,103,114],"acquisition":[25],"(SCADA)":[26],"has":[28],"been":[29],"improved":[30],"an":[31],"effective":[32],"to":[34,118],"achieve":[35,119],"fault":[36],"detection.":[37],"With":[38],"development":[40],"machine":[42],"learning":[43],"technology,":[44],"higher":[45],"accuracy":[46],"model":[49,82,107],"be":[51,116],"established":[52],"by":[53,99],"using":[54],"historic":[55],"data.":[56],"This":[57],"paper":[58],"proposes":[59],"a":[60,105],"novel":[61],"for":[65],"Long":[70],"ShortTerm":[71],"Memory":[72],"(LSTM)":[73],"algorithms.":[74],"In":[75],"terms":[76],"time":[78],"series":[79],"data,":[80],"LSTM":[81],"construct":[84],"correlation":[86],"between":[87],"prior-known":[89],"information":[90],"current":[93],"environment.":[94],"The":[95,122],"residual":[96],"signals":[97],"acquired":[98],"comparing":[100],"predicted":[102],"in":[104,130],"prediction":[106],"actual":[110],"measurements":[111],"from":[112],"SCADA":[113],"used":[117],"monitoring.":[121],"effectiveness":[123],"proposed":[126],"is":[128],"validated":[129],"case":[132],"study.":[133]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
