{"id":"https://openalex.org/W2911867527","doi":"https://doi.org/10.1109/access.2019.2893206","title":"Stacked Denoising Autoencoder With Density-Grid Based Clustering Method for Detecting Outlier of Wind Turbine Components","display_name":"Stacked Denoising Autoencoder With Density-Grid Based Clustering Method for Detecting Outlier of Wind Turbine Components","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2911867527","doi":"https://doi.org/10.1109/access.2019.2893206","mag":"2911867527"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2893206","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2893206","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08620681.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":null,"license_id":null,"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/ielx7/6287639/8600701/08620681.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102766800","display_name":"Zexian Sun","orcid":"https://orcid.org/0000-0003-0702-3347"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zexian Sun","raw_affiliation_strings":["School of Artificial Intelligence, Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-0702-3347","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101746414","display_name":"Hexu Sun","orcid":"https://orcid.org/0000-0001-7869-3036"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hexu Sun","raw_affiliation_strings":["School of Artificial Intelligence, Hebei University of Technology, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102766800"],"corresponding_institution_ids":["https://openalex.org/I184843921"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.4843,"has_fulltext":true,"cited_by_count":46,"citation_normalized_percentile":{"value":0.94084337,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"13078","last_page":"13091"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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":0.9980000257492065,"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/T11941","display_name":"Power System Reliability and Maintenance","score":0.9678999781608582,"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/outlier","display_name":"Outlier","score":0.7704303860664368},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7015846967697144},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6800240278244019},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6487156748771667},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6127098202705383},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5609472990036011},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5347278118133545},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5330632328987122},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5298433303833008},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5125829577445984},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5049026608467102},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.4637364149093628},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.4108850955963135},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19789034128189087},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.16988560557365417},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15914833545684814},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1030278205871582}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7704303860664368},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7015846967697144},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6800240278244019},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6487156748771667},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6127098202705383},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5609472990036011},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5347278118133545},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5330632328987122},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5298433303833008},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5125829577445984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5049026608467102},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.4637364149093628},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.4108850955963135},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19789034128189087},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.16988560557365417},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15914833545684814},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1030278205871582},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2893206","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2893206","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08620681.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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7cff3f08acbe49f0ac8c2422e38bde0b","is_oa":true,"landing_page_url":"https://doaj.org/article/7cff3f08acbe49f0ac8c2422e38bde0b","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 7, Pp 13078-13091 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2893206","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2893206","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08620681.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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G6410233782","display_name":null,"funder_award_id":"F2018202206","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"}],"funders":[{"id":"https://openalex.org/F4320322163","display_name":"Natural Science Foundation of Hebei Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2911867527.pdf","grobid_xml":"https://content.openalex.org/works/W2911867527.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1970541710","https://openalex.org/W2047464604","https://openalex.org/W2099085654","https://openalex.org/W2122646361","https://openalex.org/W2131132457","https://openalex.org/W2366301600","https://openalex.org/W2521921023","https://openalex.org/W2538771869","https://openalex.org/W2549636757","https://openalex.org/W2549789276","https://openalex.org/W2581973374","https://openalex.org/W2599646198","https://openalex.org/W2604784005","https://openalex.org/W2622370560","https://openalex.org/W2719445145","https://openalex.org/W2737654582","https://openalex.org/W2747276445","https://openalex.org/W2747648188","https://openalex.org/W2763099889","https://openalex.org/W2796090602","https://openalex.org/W2801050875"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W3194885736","https://openalex.org/W4363671829","https://openalex.org/W4285233543","https://openalex.org/W2806873178","https://openalex.org/W2965146396","https://openalex.org/W2770818364","https://openalex.org/W4312416532","https://openalex.org/W4230838436","https://openalex.org/W4399531511"],"abstract_inverted_index":{"Different":[0],"types":[1],"of":[2,10,27,61,122,128,142],"outliers":[3,63,109],"have":[4],"existed":[5],"in":[6,64,164],"the":[7,18,23,28,36,59,62,78,87,91,99,108,120,135,140,143,150,156,165],"monitoring":[8,29,126],"data":[9,20,30,68,70,117,127,137,168],"wind":[11,130],"turbines,":[12],"which":[13],"are":[14,75,132],"not":[15],"conducive":[16],"to":[17,34,82,97,106,119,138],"follow-up":[19],"mining.":[21],"However,":[22],"complex":[24],"inner":[25],"characteristics":[26,60],"pose":[31],"major":[32],"challenges":[33],"detect":[35],"outliers.":[37],"To":[38],"address":[39],"this":[40],"problem,":[41],"an":[42],"unsupervised":[43,171],"outlier":[44],"detection":[45],"approach":[46],"combining":[47],"stacked":[48],"denoising":[49],"autoencoder":[50],"(SDAE)":[51],"and":[52,67,115,161],"density-grid-based":[53,92],"clustering":[54,93,100],"method":[55,94],"is":[56,80,95,104],"proposed.":[57],"First,":[58],"supervisory":[65],"control":[66],"acquisition":[69],"caused":[71],"by":[72,85,170],"different":[73],"reasons":[74],"analyzed.":[76],"Then,":[77],"SDAE":[79],"utilized":[81],"extract":[83],"features":[84],"training":[86,136],"original":[88],"data.":[89,124],"Furthermore,":[90],"applied":[96],"achieve":[98],"results.":[101],"Window":[102],"width":[103],"added":[105],"classify":[107],"as":[110,134],"isolated":[111,157],"outliers,":[112,158],"missing":[113,159],"data,":[114,160],"fault":[116,162],"according":[118],"duration":[121],"abnormal":[123],"The":[125,146],"four":[129],"turbines":[131],"sampled":[133],"demonstrate":[139],"effectiveness":[141],"proposed":[144,151],"method.":[145],"results":[147],"show":[148],"that":[149],"model":[152],"can":[153],"effectively":[154],"identify":[155],"information":[163],"high":[166],"dimensional":[167],"set":[169],"learning.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}