{"id":"https://openalex.org/W4285267846","doi":"https://doi.org/10.1109/tsg.2022.3182787","title":"Dual-Channel Convolutional Network-Based Fault Cause Identification for Active Distribution System Using Realistic Waveform Measurements","display_name":"Dual-Channel Convolutional Network-Based Fault Cause Identification for Active Distribution System Using Realistic Waveform Measurements","publication_year":2022,"publication_date":"2022-06-14","ids":{"openalex":"https://openalex.org/W4285267846","doi":"https://doi.org/10.1109/tsg.2022.3182787"},"language":"en","primary_location":{"id":"doi:10.1109/tsg.2022.3182787","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2022.3182787","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Smart Grid","raw_type":"journal-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/A5114377957","display_name":"Hao Liu","orcid":"https://orcid.org/0000-0002-9569-3430"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Liu","raw_affiliation_strings":["State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101579645","display_name":"Shuo Liu","orcid":"https://orcid.org/0000-0002-6124-4848"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Liu","raw_affiliation_strings":["State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042402520","display_name":"Junbo Zhao","orcid":"https://orcid.org/0000-0002-8498-9666"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junbo Zhao","raw_affiliation_strings":["Electrical and Computer Engineering, University of Connecticut, Storrs, CT, USA"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077234408","display_name":"Tianshu Bi","orcid":"https://orcid.org/0000-0002-3555-9045"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianshu Bi","raw_affiliation_strings":["State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045026873","display_name":"Xijuan Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xijuan Yu","raw_affiliation_strings":["Power Grid Technology Center, State Grid Beijing Electric Power Research Institute, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Power Grid Technology Center, State Grid Beijing Electric Power Research Institute, Beijing, China","institution_ids":["https://openalex.org/I17442442"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5114377957"],"corresponding_institution_ids":["https://openalex.org/I153473198"],"apc_list":null,"apc_paid":null,"fwci":4.8527,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.95729393,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"13","issue":"6","first_page":"4899","last_page":"4908"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10972","display_name":"Power Systems Fault Detection","score":0.9998999834060669,"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/T10972","display_name":"Power Systems Fault Detection","score":0.9998999834060669,"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/T13183","display_name":"Islanding Detection in Power Systems","score":0.9979000091552734,"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/T11343","display_name":"Power Transformer Diagnostics and Insulation","score":0.9966999888420105,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.7405290603637695},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6623915433883667},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6258441805839539},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6015215516090393},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.5646705627441406},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5628165006637573},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.5351513028144836},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5090877413749695},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.504414439201355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4939902424812317},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4346921145915985},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.4312218427658081},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.34309127926826477},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.27792078256607056},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24700558185577393},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.10657784342765808},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10485836863517761},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07712173461914062}],"concepts":[{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.7405290603637695},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6623915433883667},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6258441805839539},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6015215516090393},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.5646705627441406},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5628165006637573},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5351513028144836},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5090877413749695},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.504414439201355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4939902424812317},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4346921145915985},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.4312218427658081},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.34309127926826477},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.27792078256607056},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24700558185577393},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.10657784342765808},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10485836863517761},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07712173461914062},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","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/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsg.2022.3182787","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsg.2022.3182787","pdf_url":null,"source":{"id":"https://openalex.org/S59604973","display_name":"IEEE Transactions on Smart Grid","issn_l":"1949-3053","issn":["1949-3053","1949-3061"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Smart Grid","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1737743232","display_name":null,"funder_award_id":"51725702","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1964437884","https://openalex.org/W2075448888","https://openalex.org/W2096256082","https://openalex.org/W2097938550","https://openalex.org/W2100395246","https://openalex.org/W2100654063","https://openalex.org/W2123625993","https://openalex.org/W2126476091","https://openalex.org/W2129298630","https://openalex.org/W2156530876","https://openalex.org/W2315621489","https://openalex.org/W2513260314","https://openalex.org/W2522034504","https://openalex.org/W2524447200","https://openalex.org/W2543283563","https://openalex.org/W2565779437","https://openalex.org/W2764582432","https://openalex.org/W2791400636","https://openalex.org/W2911027487","https://openalex.org/W2920868647","https://openalex.org/W2935316086","https://openalex.org/W2940908842","https://openalex.org/W2948852829","https://openalex.org/W2970298397","https://openalex.org/W2990832264","https://openalex.org/W3022676760","https://openalex.org/W3023170583","https://openalex.org/W3153631680","https://openalex.org/W3199382555","https://openalex.org/W3202101445","https://openalex.org/W3208121597","https://openalex.org/W4233501705"],"related_works":["https://openalex.org/W2980984853","https://openalex.org/W2326454079","https://openalex.org/W564939545","https://openalex.org/W2533590149","https://openalex.org/W3167466058","https://openalex.org/W2560154230","https://openalex.org/W2029494570","https://openalex.org/W2129331087","https://openalex.org/W2024367938","https://openalex.org/W2355447608"],"abstract_inverted_index":{"Accurate":[0],"and":[1,60,136],"rapid":[2],"identification":[3,19,49],"of":[4,63,73,133,149],"distribution":[5,45],"system":[6,13,46],"fault":[7,17,47,58,65],"causes":[8,66],"is":[9,82,126],"essential":[10],"for":[11,44,97],"power":[12,28],"reliability":[14],"enhancement.":[15],"Manual":[16],"cause":[18,48],"requires":[20],"extensive":[21],"human":[22],"resources":[23],"that":[24],"leads":[25,104],"to":[26,84,105,128],"extended":[27],"outage":[29],"time.":[30],"To":[31],"this":[32,34],"end,":[33],"paper":[35],"proposes":[36],"a":[37,121],"dual-channel":[38],"convolutional":[39],"neural":[40],"network":[41],"(DC-CNN)-based":[42],"method":[43,152],"using":[50,143],"realistic":[51],"data":[52,96,145],"from":[53],"waveform":[54,61,75],"measurement":[55],"units.":[56],"The":[57,77],"mechanism":[59],"characteristics":[62],"different":[64],"are":[67,90],"investigated":[68],"by":[69],"analyzing":[70],"large":[71],"amounts":[72],"field":[74,144],"data.":[76],"short-time":[78],"Fourier":[79],"transform":[80],"(STFT)":[81],"advocated":[83],"extract":[85],"the":[86,94,99,110,130,147,150],"frequency-domain":[87],"features,":[88],"which":[89],"used":[91],"together":[92],"with":[93,120],"time-domain":[95],"constructing":[98],"time-frequency":[100],"feature":[101,107],"images.":[102],"This":[103],"improved":[106],"extraction":[108],"via":[109],"proposed":[111,151],"DC-CNN-enabled":[112],"multimodal":[113],"information":[114],"fusion.":[115],"A":[116],"fully":[117],"connected":[118],"layer":[119],"maxout":[122],"unit":[123],"(FCM":[124],"layer)":[125],"constructed":[127],"enhance":[129],"mapping":[131],"ability":[132],"high-level":[134],"features":[135],"improve":[137],"classification":[138],"accuracy.":[139],"Extensive":[140],"test":[141],"results":[142],"demonstrate":[146],"superiority":[148],"over":[153],"other":[154],"methods.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}