{"id":"https://openalex.org/W4388279947","doi":"https://doi.org/10.1109/safeprocess58597.2023.10295720","title":"Electric submersible pump anomaly monitoring based on unsupervised multivariate streaming data analysis","display_name":"Electric submersible pump anomaly monitoring based on unsupervised multivariate streaming data analysis","publication_year":2023,"publication_date":"2023-09-22","ids":{"openalex":"https://openalex.org/W4388279947","doi":"https://doi.org/10.1109/safeprocess58597.2023.10295720"},"language":"en","primary_location":{"id":"doi:10.1109/safeprocess58597.2023.10295720","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/safeprocess58597.2023.10295720","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","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/A5100661434","display_name":"Qiang Li","orcid":"https://orcid.org/0000-0001-8751-161X"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiang Li","raw_affiliation_strings":["China University of Petroleum,College of Information Science and Engineering,Beijing,China","College of Information Science and Engineering, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China University of Petroleum,College of Information Science and Engineering,Beijing,China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"College of Information Science and Engineering, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049402891","display_name":"Jun Fu","orcid":"https://orcid.org/0000-0002-5200-4623"},"institutions":[{"id":"https://openalex.org/I4210128260","display_name":"Tianjin Energy Investment Group (China)","ror":"https://ror.org/03hmm9666","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128260"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Fu","raw_affiliation_strings":["Engineering Technology Branch of CNOOC Energy Development Co., Ltd.,Tianjin,China","Engineering Technology Branch of CNOOC Energy Development Co., Ltd., Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Engineering Technology Branch of CNOOC Energy Development Co., Ltd.,Tianjin,China","institution_ids":["https://openalex.org/I4210128260"]},{"raw_affiliation_string":"Engineering Technology Branch of CNOOC Energy Development Co., Ltd., Tianjin, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101618647","display_name":"Rong Zhang","orcid":"https://orcid.org/0000-0002-8136-0643"},"institutions":[{"id":"https://openalex.org/I4210128260","display_name":"Tianjin Energy Investment Group (China)","ror":"https://ror.org/03hmm9666","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128260"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Zhang","raw_affiliation_strings":["Engineering Technology Branch of CNOOC Energy Development Co., Ltd.,Tianjin,China","Engineering Technology Branch of CNOOC Energy Development Co., Ltd., Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Engineering Technology Branch of CNOOC Energy Development Co., Ltd.,Tianjin,China","institution_ids":["https://openalex.org/I4210128260"]},{"raw_affiliation_string":"Engineering Technology Branch of CNOOC Energy Development Co., Ltd., Tianjin, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090316857","display_name":"Hongtai Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I157771985","display_name":"China National Nuclear Corporation","ror":"https://ror.org/01d5ymp84","country_code":"CN","type":"government","lineage":["https://openalex.org/I157771985"]},{"id":"https://openalex.org/I98227222","display_name":"China National Petroleum Corporation (China)","ror":"https://ror.org/05269d038","country_code":"CN","type":"company","lineage":["https://openalex.org/I98227222"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"HongTai Liu","raw_affiliation_strings":["Research Institute of Safety and Environment Technology,China National Petroleum Corporation,Beijing,China","China National Petroleum Corporation, Research Institute of Safety and Environment Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research Institute of Safety and Environment Technology,China National Petroleum Corporation,Beijing,China","institution_ids":["https://openalex.org/I157771985"]},{"raw_affiliation_string":"China National Petroleum Corporation, Research Institute of Safety and Environment Technology, Beijing, China","institution_ids":["https://openalex.org/I98227222"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103438920","display_name":"Yong Li","orcid":"https://orcid.org/0000-0002-2380-2474"},"institutions":[{"id":"https://openalex.org/I157771985","display_name":"China National Nuclear Corporation","ror":"https://ror.org/01d5ymp84","country_code":"CN","type":"government","lineage":["https://openalex.org/I157771985"]},{"id":"https://openalex.org/I98227222","display_name":"China National Petroleum Corporation (China)","ror":"https://ror.org/05269d038","country_code":"CN","type":"company","lineage":["https://openalex.org/I98227222"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["Research Institute of Safety and Environment Technology,China National Petroleum Corporation,Beijing,China","China National Petroleum Corporation, Research Institute of Safety and Environment Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research Institute of Safety and Environment Technology,China National Petroleum Corporation,Beijing,China","institution_ids":["https://openalex.org/I157771985"]},{"raw_affiliation_string":"China National Petroleum Corporation, Research Institute of Safety and Environment Technology, Beijing, China","institution_ids":["https://openalex.org/I98227222"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077924144","display_name":"Xiaoyong Gao","orcid":"https://orcid.org/0000-0002-6893-4139"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"XiaoYong Gao","raw_affiliation_strings":["China University of Petroleum,College of Information Science and Engineering,Beijing,China","College of Information Science and Engineering, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China University of Petroleum,College of Information Science and Engineering,Beijing,China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"College of Information Science and Engineering, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100661434"],"corresponding_institution_ids":["https://openalex.org/I204553293"],"apc_list":null,"apc_paid":null,"fwci":0.5634,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67201923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9983000159263611,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9983000159263611,"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/T11220","display_name":"Water Systems and Optimization","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T13050","display_name":"Oil and Gas Production Techniques","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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":0.7206307649612427},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.618057370185852},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5812274217605591},{"id":"https://openalex.org/keywords/lift","display_name":"Lift (data mining)","score":0.5181190371513367},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.485897958278656},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4834080934524536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47058218717575073},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4114006757736206},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3738742768764496},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2109588384628296}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7206307649612427},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.618057370185852},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5812274217605591},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.5181190371513367},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.485897958278656},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4834080934524536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47058218717575073},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4114006757736206},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3738742768764496},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2109588384628296},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/safeprocess58597.2023.10295720","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/safeprocess58597.2023.10295720","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5699999928474426}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1597576211","https://openalex.org/W1689197954","https://openalex.org/W1808644423","https://openalex.org/W1968914084","https://openalex.org/W1993573509","https://openalex.org/W2015785348","https://openalex.org/W2024599312","https://openalex.org/W2025967380","https://openalex.org/W2082563543","https://openalex.org/W2167101736","https://openalex.org/W2269445348","https://openalex.org/W2808547671","https://openalex.org/W2911627187","https://openalex.org/W2945020349","https://openalex.org/W3096197601","https://openalex.org/W3183757650","https://openalex.org/W4233786811","https://openalex.org/W4280501636","https://openalex.org/W4291109999","https://openalex.org/W4291710931","https://openalex.org/W4313216081","https://openalex.org/W6675340555"],"related_works":["https://openalex.org/W4389397071","https://openalex.org/W2105642232","https://openalex.org/W3197833032","https://openalex.org/W3207332793","https://openalex.org/W2023045191","https://openalex.org/W4386081464","https://openalex.org/W2952839243","https://openalex.org/W2499612753","https://openalex.org/W2750709484","https://openalex.org/W3113278055"],"abstract_inverted_index":{"Electric":[0],"Submersible":[1],"Pump":[2],"is":[3,17,88,117],"an":[4],"essential":[5],"artificial":[6],"lift":[7],"equipment":[8],"in":[9,90,141,154,162],"the":[10,45,53,66,69,80,83,86,93,112,120,124,132,135,151,166,172,177],"petroleum":[11],"industry,":[12],"and":[13,25,58,76,164,176],"its":[14],"anomaly":[15],"detection":[16,96],"of":[18,68,85,103,168],"great":[19],"significance":[20],"for":[21,55,184],"maintaining":[22],"system":[23,70,159],"performance":[24,160],"ensuring":[26],"normal":[27],"production.":[28],"In":[29],"this":[30,155],"paper,":[31],"we":[32],"propose":[33],"a":[34],"novel":[35],"unsupervised":[36],"multivariate":[37],"streaming":[38],"data":[39,48],"analysis":[40],"approach":[41],"that":[42,63,150],"directly":[43],"uses":[44],"raw":[46],"structured":[47],"as":[49],"input.":[50],"It":[51],"eliminates":[52],"need":[54],"complex":[56],"modeling":[57],"parameter":[59],"optimization.":[60],"Then,":[61],"metrics":[62],"can":[64,157],"reflect":[65],"state":[67],"are":[71],"built":[72],"through":[73],"feature":[74,113],"mapping":[75],"fusion.":[77],"Based":[78],"on":[79],"fused":[81],"metric,":[82],"smoothness":[84],"metric":[87],"monitored":[89],"real-time":[91],"by":[92],"control":[94],"chart":[95],"method,":[97],"which":[98],"does":[99],"not":[100],"require":[101],"pre-training":[102],"known":[104],"label":[105],"samples":[106],"or":[107],"any":[108],"domain":[109],"knowledge.":[110],"Finally,":[111],"selection":[114],"algorithm":[115,121,133,152],"ANOVA":[116],"introduced":[118],"into":[119],"to":[122,128],"locate":[123],"most":[125],"relevant":[126],"features":[127],"anomalies.":[129],"We":[130],"evaluate":[131],"using":[134],"ESP":[136],"signals":[137],"from":[138],"three":[139],"regions":[140],"Penglai,":[142],"Bohai":[143],"Oilfield,":[144],"China.":[145],"The":[146],"experimental":[147],"results":[148],"show":[149],"proposed":[153],"paper":[156],"capture":[158],"anomalies":[161],"time":[163],"realize":[165],"location":[167],"suspicious":[169],"features.":[170],"Moreover,":[171],"inexpensive":[173],"computational":[174],"costs":[175],"second-level":[178],"inspection":[179],"speed":[180],"make":[181],"it":[182],"ideal":[183],"on-site":[185],"deployment.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-02-07T06:11:34.122080","created_date":"2025-10-10T00:00:00"}