{"id":"https://openalex.org/W4381884103","doi":"https://doi.org/10.1109/access.2023.3288852","title":"Fault Classification in Distribution Systems Using Deep Learning With Data Preprocessing Methods Based on Fast Dynamic Time Warping and Short-Time Fourier Transform","display_name":"Fault Classification in Distribution Systems Using Deep Learning With Data Preprocessing Methods Based on Fast Dynamic Time Warping and Short-Time Fourier Transform","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4381884103","doi":"https://doi.org/10.1109/access.2023.3288852"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3288852","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3288852","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10160003.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/ielx7/6287639/6514899/10160003.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062878528","display_name":"Nien\u2010Che Yang","orcid":"https://orcid.org/0000-0002-5006-9044"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Nien-Che Yang","raw_affiliation_strings":["Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103255523","display_name":"J. C. Yang","orcid":"https://orcid.org/0009-0001-6750-7856"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jen-Ming Yang","raw_affiliation_strings":["Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I154864474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062878528"],"corresponding_institution_ids":["https://openalex.org/I154864474"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.1132,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.97370892,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"11","issue":null,"first_page":"63612","last_page":"63622"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994000196456909,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994000196456909,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9940000176429749,"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/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9812999963760376,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7918663620948792},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.6809252500534058},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6513702273368835},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6000913381576538},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5678139925003052},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5202492475509644},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.5134885907173157},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.4801749289035797},{"id":"https://openalex.org/keywords/discrete-fourier-transform","display_name":"Discrete Fourier transform (general)","score":0.4533906579017639},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.452620267868042},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.43914899230003357},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.43045198917388916},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.3504956364631653},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3340630829334259},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3295489251613617},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.1557585597038269},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.088369220495224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7918663620948792},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.6809252500534058},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6513702273368835},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6000913381576538},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5678139925003052},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5202492475509644},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.5134885907173157},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.4801749289035797},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.4533906579017639},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.452620267868042},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.43914899230003357},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.43045198917388916},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.3504956364631653},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3340630829334259},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3295489251613617},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.1557585597038269},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.088369220495224},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"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/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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3288852","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3288852","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10160003.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:f4fae6ba9300441289cc8e5276ec54cb","is_oa":true,"landing_page_url":"https://doaj.org/article/f4fae6ba9300441289cc8e5276ec54cb","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 63612-63622 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3288852","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3288852","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10160003.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":[{"id":"https://metadata.un.org/sdg/7","score":0.7799999713897705,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G6623606742","display_name":null,"funder_award_id":"NSTC 111-2622-8-011-014-SB","funder_id":"https://openalex.org/F4320331164","funder_display_name":"National Science and Technology Council"}],"funders":[{"id":"https://openalex.org/F4320307110","display_name":"Delta","ror":"https://ror.org/03g9c1e75"},{"id":"https://openalex.org/F4320318804","display_name":"Delta Electronics","ror":"https://ror.org/04s3g5933"},{"id":"https://openalex.org/F4320323900","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95"},{"id":"https://openalex.org/F4320324515","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49"},{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4381884103.pdf","grobid_xml":"https://content.openalex.org/works/W4381884103.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1829376396","https://openalex.org/W2008348094","https://openalex.org/W2027537551","https://openalex.org/W2144994235","https://openalex.org/W2344705789","https://openalex.org/W2619363936","https://openalex.org/W2768866948","https://openalex.org/W2794042936","https://openalex.org/W2930563906","https://openalex.org/W2940908842","https://openalex.org/W2943505802","https://openalex.org/W2969600103","https://openalex.org/W3011148068","https://openalex.org/W3024527458","https://openalex.org/W3059503398","https://openalex.org/W3088922629","https://openalex.org/W3097239744","https://openalex.org/W3097285095","https://openalex.org/W3106823864","https://openalex.org/W3110581640","https://openalex.org/W3132448432","https://openalex.org/W3135964818","https://openalex.org/W4206203292","https://openalex.org/W4212946700","https://openalex.org/W4224302837","https://openalex.org/W4283829463","https://openalex.org/W4290043189","https://openalex.org/W4309577008","https://openalex.org/W4311903141"],"related_works":["https://openalex.org/W1670332068","https://openalex.org/W2095618524","https://openalex.org/W2735770592","https://openalex.org/W2347413598","https://openalex.org/W2330863229","https://openalex.org/W71572444","https://openalex.org/W1997383766","https://openalex.org/W2350336482","https://openalex.org/W2002136255","https://openalex.org/W2149419755"],"abstract_inverted_index":{"Traditional":[0],"fault":[1,230,242],"classification":[2,231],"methods":[3],"typically":[4],"rely":[5],"on":[6,131],"manual":[7],"feature":[8],"extraction":[9],"and":[10,24,54,65,70,93,143,169,192],"the":[11,62,74,97,105,111,132,153,160,165,193,210,220,225,229,235,238],"application":[12],"of":[13,40,114,228,237],"machine-learning":[14],"algorithms.":[15],"However,":[16,100],"these":[17],"approaches":[18],"encounter":[19],"difficulties":[20],"when":[21],"extracting":[22],"features":[23,142],"handling":[25],"large-scale":[26],"datasets.":[27],"This":[28],"study":[29,124],"proposes":[30,125],"a":[31,81,126],"data":[32,115,127,147,151,215],"preprocessing":[33],"method":[34,59,129,162,212,240],"for":[35,241],"accurately":[36],"detecting":[37],"various":[38],"types":[39],"short-circuit":[41,98],"faults":[42],"in":[43,179,203],"power":[44,52,174,183],"systems,":[45],"which":[46,139],"can":[47,163],"lead":[48],"to":[49,79,95,110,172],"more":[50],"effective":[51],"repair":[53],"maintenance":[55],"processes.":[56],"The":[57,155,198,205],"proposed":[58,161,211,239],"involves":[60],"converting":[61],"measured":[63],"voltage":[64],"current":[66],"signals":[67],"into":[68],"time":[69,135],"frequency":[71],"domains":[72],"using":[73],"short-time":[75],"Fourier":[76],"transform":[77],"(STFT)":[78],"produce":[80],"time-frequency":[82],"energy":[83],"map.":[84],"A":[85],"convolutional":[86],"neural":[87],"network":[88],"(CNN)":[89],"is":[90,201],"subsequently":[91],"trained":[92],"tested":[94,178],"classify":[96],"faults.":[99],"overfitting":[101],"may":[102],"occur":[103],"during":[104],"CNN":[106],"training":[107,167,222],"process":[108],"owing":[109],"large":[112],"volume":[113],"with":[116],"similar":[117,146],"features.":[118],"To":[119],"address":[120],"this":[121,123],"issue,":[122],"reduction":[128],"based":[130],"fast":[133],"dynamic":[134],"warping":[136],"(Fast-DTW)":[137],"algorithm,":[138],"compares":[140],"waveform":[141],"eliminates":[144],"highly":[145],"regarded":[148],"as":[149,177],"redundant":[150,214],"from":[152],"dataset.":[154],"simulation":[156,181,206],"results":[157,207],"show":[158],"that":[159,209],"improve":[164],"model":[166,221],"performance":[168],"its":[170],"adaptability":[171],"different":[173],"system":[175],"topologies,":[176],"two":[180],"environments:":[182],"systems":[184],"computer-aided":[185],"design":[186],"(PSCAD)/electromagnetic":[187],"transients,":[188],"including":[189],"DC":[190],"(EMTDC),":[191],"real-time":[194],"digital":[195],"simulator":[196],"(RTDS).":[197],"STFT":[199],"transformation":[200],"implemented":[202],"MATLAB.":[204],"demonstrate":[208],"reduces":[213],"by":[216],"40.2%,":[217],"while":[218],"decreasing":[219],"time.":[223],"Consequently,":[224],"overall":[226],"accuracy":[227],"reaches":[232],"99.37%,":[233],"confirming":[234],"effectiveness":[236],"classification.":[243]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}