{"id":"https://openalex.org/W2980831101","doi":"https://doi.org/10.23919/eusipco.2019.8903052","title":"Deep Complex Neural Network Learning for High-Voltage Insulation Fault Classification from Complex Bispectrum Representation","display_name":"Deep Complex Neural Network Learning for High-Voltage Insulation Fault Classification from Complex Bispectrum Representation","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2980831101","doi":"https://doi.org/10.23919/eusipco.2019.8903052","mag":"2980831101"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2019.8903052","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8903052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://researchonline.gcu.ac.uk/en/publications/7db4b22d-edb8-42c8-8f88-c2a4e53cef88","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010827986","display_name":"Imene Mitiche","orcid":"https://orcid.org/0000-0001-9169-835X"},"institutions":[{"id":"https://openalex.org/I195939026","display_name":"Glasgow Caledonian University","ror":"https://ror.org/03dvm1235","country_code":"GB","type":"education","lineage":["https://openalex.org/I195939026"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Imene Mitiche","raw_affiliation_strings":["School of Engineering and Built Environment, Glasgow Caledonian University, Glasgow, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering and Built Environment, Glasgow Caledonian University, Glasgow, United Kingdom","institution_ids":["https://openalex.org/I195939026"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101875183","display_name":"Mark David Jenkins","orcid":"https://orcid.org/0000-0001-9717-8523"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mark David Jenkins","raw_affiliation_strings":["Geckotech Solutions Ltd., Edinburgh, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Geckotech Solutions Ltd., Edinburgh, United Kingdom","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000142779","display_name":"Philip Boreham","orcid":"https://orcid.org/0000-0003-0071-7717"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Philip Boreham","raw_affiliation_strings":["Innovation Centre for Online Systems, Bere Regis, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Innovation Centre for Online Systems, Bere Regis, United Kingdom","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085129880","display_name":"A. Nesbitt","orcid":"https://orcid.org/0000-0003-3518-7656"},"institutions":[{"id":"https://openalex.org/I195939026","display_name":"Glasgow Caledonian University","ror":"https://ror.org/03dvm1235","country_code":"GB","type":"education","lineage":["https://openalex.org/I195939026"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alan Nesbitt","raw_affiliation_strings":["School of Engineering and Built Environment, Glasgow Caledonian University, Glasgow, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering and Built Environment, Glasgow Caledonian University, Glasgow, United Kingdom","institution_ids":["https://openalex.org/I195939026"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001283656","display_name":"Gordon Morison","orcid":"https://orcid.org/0000-0002-3282-5248"},"institutions":[{"id":"https://openalex.org/I195939026","display_name":"Glasgow Caledonian University","ror":"https://ror.org/03dvm1235","country_code":"GB","type":"education","lineage":["https://openalex.org/I195939026"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gordon Morison","raw_affiliation_strings":["School of Engineering and Built Environment, Glasgow Caledonian University, Glasgow, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering and Built Environment, Glasgow Caledonian University, Glasgow, United Kingdom","institution_ids":["https://openalex.org/I195939026"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3392,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.81062827,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9944999814033508,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9905999898910522,"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/bispectrum","display_name":"Bispectrum","score":0.994403064250946},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6669265031814575},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5933393836021423},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.586455762386322},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5718641877174377},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5408502221107483},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5166423916816711},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4920003116130829},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.434822678565979},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.4336888790130615},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4260902404785156},{"id":"https://openalex.org/keywords/electromagnetic-interference","display_name":"Electromagnetic interference","score":0.4254709482192993},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4142988920211792},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.38044285774230957},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.28673532605171204},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.12171736359596252},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.11271989345550537},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08594360947608948}],"concepts":[{"id":"https://openalex.org/C114148568","wikidata":"https://www.wikidata.org/wiki/Q2410583","display_name":"Bispectrum","level":3,"score":0.994403064250946},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6669265031814575},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5933393836021423},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.586455762386322},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5718641877174377},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5408502221107483},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5166423916816711},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4920003116130829},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.434822678565979},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.4336888790130615},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4260902404785156},{"id":"https://openalex.org/C184892835","wikidata":"https://www.wikidata.org/wiki/Q1474513","display_name":"Electromagnetic interference","level":2,"score":0.4254709482192993},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4142988920211792},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.38044285774230957},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28673532605171204},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.12171736359596252},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.11271989345550537},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08594360947608948},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.23919/eusipco.2019.8903052","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8903052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},{"id":"pmh:oai:researchonline.gcu.ac.uk:openaire/7db4b22d-edb8-42c8-8f88-c2a4e53cef88","is_oa":true,"landing_page_url":"https://researchonline.gcu.ac.uk/en/publications/7db4b22d-edb8-42c8-8f88-c2a4e53cef88","pdf_url":null,"source":{"id":"https://openalex.org/S4306402566","display_name":"ResearchOnline (Glasgow Caledonian University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I195939026","host_organization_name":"Glasgow Caledonian University","host_organization_lineage":["https://openalex.org/I195939026"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Mitiche, I, Jenkins, M D, Boreham, P, Nesbitt, A & Morison, G 2019, Deep complex neural network learning for high-voltage insulation fault classification from complex bispectrum representation. in 2019 27th European Signal Processing Conference (EUSIPCO). European Signal Processing Conference, vol. 2019-September, IEEE, 2019 27th European Signal Processing Conference (EUSIPCO), A Coruna, Spain, 2/09/19. https://doi.org/10.23919/EUSIPCO.2019.8903052","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:researchonline.gcu.ac.uk:openaire/7db4b22d-edb8-42c8-8f88-c2a4e53cef88","is_oa":true,"landing_page_url":"https://researchonline.gcu.ac.uk/en/publications/7db4b22d-edb8-42c8-8f88-c2a4e53cef88","pdf_url":null,"source":{"id":"https://openalex.org/S4306402566","display_name":"ResearchOnline (Glasgow Caledonian University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I195939026","host_organization_name":"Glasgow Caledonian University","host_organization_lineage":["https://openalex.org/I195939026"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Mitiche, I, Jenkins, M D, Boreham, P, Nesbitt, A & Morison, G 2019, Deep complex neural network learning for high-voltage insulation fault classification from complex bispectrum representation. in 2019 27th European Signal Processing Conference (EUSIPCO). European Signal Processing Conference, vol. 2019-September, IEEE, 2019 27th European Signal Processing Conference (EUSIPCO), A Coruna, Spain, 2/09/19. https://doi.org/10.23919/EUSIPCO.2019.8903052","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1974225813","https://openalex.org/W1976832178","https://openalex.org/W2051300618","https://openalex.org/W2061661003","https://openalex.org/W2064735117","https://openalex.org/W2067275923","https://openalex.org/W2071430622","https://openalex.org/W2112323438","https://openalex.org/W2171640671","https://openalex.org/W2280498816","https://openalex.org/W2393256679","https://openalex.org/W2513513181","https://openalex.org/W2546651588","https://openalex.org/W2590099141","https://openalex.org/W2754361766","https://openalex.org/W2810566158","https://openalex.org/W2888864352","https://openalex.org/W2962913459","https://openalex.org/W6733684993","https://openalex.org/W6738884980"],"related_works":["https://openalex.org/W2541615194","https://openalex.org/W2357592863","https://openalex.org/W2002943794","https://openalex.org/W2351984395","https://openalex.org/W2544518984","https://openalex.org/W2371303008","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983"],"abstract_inverted_index":{"Bispectrum":[0,21,42,109,117,137],"representations":[1,118],"previously":[2],"achieved":[3],"a":[4,25,28,51,88,108,125,170],"successful":[5],"classification":[6,127,143,160],"of":[7,19,41,64,71,135,144,169],"insulation":[8,83],"fault":[9],"signals":[10,79,153],"in":[11,37,87,162],"High-Voltage":[12],"(HV)":[13,74],"power":[14,75,90],"plant.":[15],"The":[16,148],"magnitude":[17],"information":[18],"the":[20,39,62,93,113,119,132,142,167],"was":[22],"implemented":[23,49],"as":[24,43,124],"feature":[26],"for":[27,131],"Deep":[29,52],"Neural":[30,56],"Network.":[31],"This":[32,59,129],"preliminary":[33],"research":[34],"brought":[35],"interest":[36],"evaluating":[38],"performance":[40,168],"complex":[44,136],"input":[45],"features":[46],"that":[47],"are":[48,85],"into":[50],"Complex":[53],"Valued":[54,172],"Convolutional":[55],"Network":[57],"(CV-CNN).":[58],"paper":[60],"presents":[61],"application":[63],"this":[65],"novel":[66,133],"method":[67,97],"to":[68,81,106,116,141],"condition":[69],"monitoring":[70],"High":[72],"Voltage":[73],"plant":[76,91],"equipment.":[77],"Discharge":[78],"related":[80],"HV":[82,145],"faults":[84],"measured":[86],"real-world":[89],"using":[92,100],"Electromagnetic":[94],"Interference":[95],"(EMI)":[96],"and":[98,138,157],"processed":[99],"third":[101],"order":[102],"Higher-Order":[103],"Statistics":[104],"(HOS)":[105],"obtain":[107],"representation.":[110],"By":[111],"mapping":[112],"time-domain":[114],"signal":[115],"problem":[120],"can":[121],"be":[122],"approached":[123],"complex-valued":[126],"task.":[128],"allows":[130],"combination":[134],"CV-CNN":[139],"applied":[140],"discharge":[146],"signals.":[147],"network":[149],"is":[150],"trained":[151],"on":[152],"from":[154],"9":[155],"classes":[156],"achieves":[158],"high":[159],"accuracy":[161],"each":[163],"category,":[164],"improving":[165],"upon":[166],"Real":[171],"CNN":[173],"(RV-CNN).":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}