{"id":"https://openalex.org/W3090633514","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207487","title":"A Comparison of GANs-Based Approaches for Combustor System Fault Detection","display_name":"A Comparison of GANs-Based Approaches for Combustor System Fault Detection","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3090633514","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207487","mag":"3090633514"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9207487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5100745350","display_name":"Rui Xu","orcid":"https://orcid.org/0000-0003-0516-3629"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rui Xu","raw_affiliation_strings":["Artificial Intelligence & Machine Learning Laboratory, GE Research, Niskayuna, NY, USA"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence & Machine Learning Laboratory, GE Research, Niskayuna, NY, USA","institution_ids":["https://openalex.org/I4210134512"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073342710","display_name":"Weizhong Yan","orcid":"https://orcid.org/0000-0002-7916-8476"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weizhong Yan","raw_affiliation_strings":["Artificial Intelligence & Machine Learning Laboratory, GE Research, Niskayuna, NY, USA"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence & Machine Learning Laboratory, GE Research, Niskayuna, NY, USA","institution_ids":["https://openalex.org/I4210134512"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100745350"],"corresponding_institution_ids":["https://openalex.org/I4210134512"],"apc_list":null,"apc_paid":null,"fwci":0.5302,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.73143186,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9807999730110168,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9700999855995178,"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/anomaly-detection","display_name":"Anomaly detection","score":0.756783664226532},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7088067531585693},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.6939225792884827},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.555154025554657},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5206479430198669},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5065878629684448},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4320865571498871},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38082191348075867},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07718014717102051}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.756783664226532},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7088067531585693},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.6939225792884827},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.555154025554657},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5206479430198669},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5065878629684448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4320865571498871},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38082191348075867},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07718014717102051},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9207487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W2015887370","https://openalex.org/W2063191991","https://openalex.org/W2089554624","https://openalex.org/W2099471712","https://openalex.org/W2104834593","https://openalex.org/W2115627867","https://openalex.org/W2122646361","https://openalex.org/W2127064699","https://openalex.org/W2136647532","https://openalex.org/W2137130182","https://openalex.org/W2156947582","https://openalex.org/W2166406766","https://openalex.org/W2187089797","https://openalex.org/W2520707650","https://openalex.org/W2556077447","https://openalex.org/W2577946330","https://openalex.org/W2599354622","https://openalex.org/W2619371851","https://openalex.org/W2746068898","https://openalex.org/W2787947370","https://openalex.org/W2902758299","https://openalex.org/W2910068345","https://openalex.org/W2949099979","https://openalex.org/W2954278343","https://openalex.org/W2963045681","https://openalex.org/W2963170156","https://openalex.org/W2963265008","https://openalex.org/W2963523189","https://openalex.org/W3006520502","https://openalex.org/W3174658763","https://openalex.org/W4294568686","https://openalex.org/W4320013936","https://openalex.org/W6715501732","https://openalex.org/W6726983635","https://openalex.org/W6732248266","https://openalex.org/W6735108248","https://openalex.org/W6738597727","https://openalex.org/W6743002019","https://openalex.org/W6748293363","https://openalex.org/W6748495906","https://openalex.org/W6751917112","https://openalex.org/W6758101687","https://openalex.org/W6797107569"],"related_works":["https://openalex.org/W2032233321","https://openalex.org/W3121970507","https://openalex.org/W2110028391","https://openalex.org/W54497855","https://openalex.org/W217960748","https://openalex.org/W3125814499","https://openalex.org/W2090827041","https://openalex.org/W2094012830","https://openalex.org/W187246281","https://openalex.org/W2079194830"],"abstract_inverted_index":{"In":[0,77],"manufacturing":[1],"industry,":[2],"anomaly":[3,37,87],"detection":[4,38,88,98],"(AD)":[5],"has":[6],"been":[7],"widely":[8],"applied":[9],"to":[10,34],"monitor":[11],"asset":[12],"operation":[13],"status":[14],"and":[15,61],"provide":[16],"decision":[17],"support":[18],"for":[19,90,146],"proactive":[20],"maintenance.":[21],"However,":[22,136],"the":[23,35,41,82,100,114,119,127,151],"extreme":[24],"complexities":[25],"of":[26,55,67,84,99,103,116,141,153],"many":[27,32],"industrial":[28,93],"assets":[29],"have":[30,49],"raised":[31],"challenges":[33],"classical":[36],"approaches.":[39],"For":[40],"past":[42],"several":[43],"years,":[44],"generative":[45],"adversarial":[46],"networks":[47],"(GANs)":[48],"achieved":[50],"breakthrough":[51],"in":[52,69,106],"a":[53,91,133,138],"variety":[54],"applications,":[56],"such":[57],"as":[58],"image":[59],"generation":[60],"video":[62],"prediction.":[63],"Some":[64],"initial":[65],"applications":[66],"GANs":[68,154],"image-related":[70],"AD":[71],"problems":[72],"also":[73],"show":[74,111],"promising":[75],"results.":[76],"this":[78],"paper,":[79],"we":[80,148],"investigated":[81],"performance":[83,152],"three":[85,120],"GANs-based":[86],"approaches":[89,121],"specific":[92],"use":[94],"case":[95],"-":[96],"fault":[97,142],"combustion":[101],"system":[102],"gas":[104,134],"turbines":[105],"power":[107],"plants.":[108],"The":[109],"results":[110],"that":[112,150],"under":[113],"framework":[115],"semi-supervised":[117],"learning,":[118],"do":[122],"not":[123],"perform":[124],"well":[125],"on":[126],"one-year":[128],"field":[129],"data":[130,143],"collected":[131],"from":[132],"turbine.":[135],"if":[137],"small":[139],"portion":[140],"is":[144,155],"provided":[145],"training,":[147],"observe":[149],"significantly":[156],"improved.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
