{"id":"https://openalex.org/W3027820774","doi":"https://doi.org/10.1109/tim.2020.2996717","title":"Partial Discharge Signal Denoising Based on Singular Value Decomposition and Empirical Wavelet Transform","display_name":"Partial Discharge Signal Denoising Based on Singular Value Decomposition and Empirical Wavelet Transform","publication_year":2020,"publication_date":"2020-05-22","ids":{"openalex":"https://openalex.org/W3027820774","doi":"https://doi.org/10.1109/tim.2020.2996717","mag":"3027820774"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2020.2996717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.2996717","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5103071400","display_name":"Jun Zhong","orcid":"https://orcid.org/0000-0001-5040-8299"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhong","raw_affiliation_strings":["School of Electrical Engineering, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-5040-8299","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035863469","display_name":"Xiaowen Bi","orcid":"https://orcid.org/0000-0002-3300-4441"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowen Bi","raw_affiliation_strings":["School of Electrical Engineering, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-3300-4441","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013348434","display_name":"Qin Shu","orcid":"https://orcid.org/0000-0002-7225-6043"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qin Shu","raw_affiliation_strings":["School of Electrical Engineering, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-7225-6043","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090816356","display_name":"Minwei Chen","orcid":"https://orcid.org/0000-0002-5700-6142"},"institutions":[{"id":"https://openalex.org/I4210111970","display_name":"Fujian Electric Power Survey & Design Institute","ror":"https://ror.org/0233jyt67","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210111970"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minwei Chen","raw_affiliation_strings":["State Grid Fujian Electric Power Research Institute, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5700-6142","affiliations":[{"raw_affiliation_string":"State Grid Fujian Electric Power Research Institute, Fuzhou, China","institution_ids":["https://openalex.org/I4210111970"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103201261","display_name":"Dianbo Zhou","orcid":"https://orcid.org/0000-0002-6403-3843"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dianbo Zhou","raw_affiliation_strings":["State Grid Sichuan Electric Power Research Institute, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-6403-3843","affiliations":[{"raw_affiliation_string":"State Grid Sichuan Electric Power Research Institute, Chengdu, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030183406","display_name":"Dakun Zhang","orcid":"https://orcid.org/0000-0002-4308-5900"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dakun Zhang","raw_affiliation_strings":["Chengdu Ruichi Technology Company Ltd., Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-4308-5900","affiliations":[{"raw_affiliation_string":"Chengdu Ruichi Technology Company Ltd., Chengdu, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.0838,"has_fulltext":false,"cited_by_count":125,"citation_normalized_percentile":{"value":0.95517181,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"69","issue":"11","first_page":"8866","last_page":"8873"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10511","display_name":"High voltage insulation and dielectric phenomena","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10511","display_name":"High voltage insulation and dielectric phenomena","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11343","display_name":"Power Transformer Diagnostics and Insulation","score":0.9945999979972839,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9943000078201294,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.6177741289138794},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5940752625465393},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5605782866477966},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5189780592918396},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5022780895233154},{"id":"https://openalex.org/keywords/aliasing","display_name":"Aliasing","score":0.4844529628753662},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.45096355676651},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4407652020454407},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43343502283096313},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4330940544605255},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.41367560625076294},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40373995900154114},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37981700897216797},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3704606890678406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35609498620033264},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.30928751826286316},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.2495785355567932},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.13888439536094666},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11958792805671692}],"concepts":[{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.6177741289138794},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5940752625465393},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5605782866477966},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5189780592918396},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5022780895233154},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.4844529628753662},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.45096355676651},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4407652020454407},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43343502283096313},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4330940544605255},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.41367560625076294},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40373995900154114},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37981700897216797},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3704606890678406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35609498620033264},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.30928751826286316},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2495785355567932},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.13888439536094666},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11958792805671692},{"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2020.2996717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.2996717","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1937931689","https://openalex.org/W1975374405","https://openalex.org/W1990985215","https://openalex.org/W2019900743","https://openalex.org/W2025016692","https://openalex.org/W2047132953","https://openalex.org/W2058214001","https://openalex.org/W2104752620","https://openalex.org/W2114723491","https://openalex.org/W2154780922","https://openalex.org/W2159437955","https://openalex.org/W2160725657","https://openalex.org/W2209482248","https://openalex.org/W2466433409","https://openalex.org/W2901296148","https://openalex.org/W2909400870","https://openalex.org/W2927328165","https://openalex.org/W2942803188","https://openalex.org/W2943250598","https://openalex.org/W2972291529","https://openalex.org/W2987190105","https://openalex.org/W4255234954","https://openalex.org/W6675570070"],"related_works":["https://openalex.org/W1577789985","https://openalex.org/W1970278134","https://openalex.org/W1974556001","https://openalex.org/W2360116365","https://openalex.org/W2368855668","https://openalex.org/W1601003161","https://openalex.org/W2390482320","https://openalex.org/W2041988345","https://openalex.org/W2112061901","https://openalex.org/W1998102702"],"abstract_inverted_index":{"Online":[0],"partial":[1],"discharge":[2],"(PD)":[3],"monitoring":[4],"is":[5,15,32,49,123,139,153,188],"an":[6],"important":[7],"means":[8],"to":[9,17,23,34,95,110,145,155],"detect":[10],"insulation":[11],"deterioration.":[12],"However,":[13],"it":[14],"difficult":[16],"extract":[18],"the":[19,27,36,43,63,72,79,82,118,127,136,157,163,181,185,204],"PD":[20,30,47,55,60,128,175,186],"signal":[21,31,48,129,138,176,187],"due":[22],"various":[24],"interferences":[25],"in":[26,53],"field.":[28],"Noisy":[29],"used":[33,154],"judge":[35],"status":[37],"of":[38,84,174,207],"insulation,":[39],"which":[40],"would":[41],"affect":[42],"conclusion;":[44],"therefore,":[45],"denoising":[46,61,73],"a":[50,93,168],"major":[51],"task":[52],"online":[54],"monitoring.":[56],"Common":[57],"methods":[58],"for":[59,126],"include":[62],"empirical":[64,119],"mode":[65],"decomposition":[66,88,108],"(EMD)":[67],"and":[68,87,114,162,198],"wavelet":[69,120],"transform;":[70],"however,":[71],"results":[74,194],"are":[75,165,177],"highly":[76],"dependent":[77],"on":[78],"modal":[80],"aliasing,":[81],"selection":[83],"mother":[85],"wavelets,":[86],"levels.":[89],"This":[90,99],"article":[91],"proposes":[92],"method":[94,100],"solve":[96],"these":[97],"problems.":[98],"uses":[101],"traditionally":[102],"singular":[103],"value":[104,107],"transform":[105,121],"[singular":[106],"(SVD)]":[109],"reconstruct":[111],"narrowband":[112],"interference":[113],"remove":[115],"it.":[116],"Next,":[117],"(EWT)":[122],"carried":[124],"out":[125],"that":[130],"has":[131],"residual":[132],"white":[133],"noise.":[134],"Then,":[135],"noisy":[137],"decomposed":[140],"into":[141,167],"several":[142],"modes":[143,158,164],"corresponding":[144],"each":[146],"spectrum":[147],"segment.":[148],"The":[149,171,193],"$3~\\sigma":[150],"$":[151],"principle":[152],"denoise":[156],"with":[159],"large":[160],"kurtosis,":[161],"combined":[166],"reference":[169,182],"signal.":[170,183],"start-end":[172],"positions":[173],"then":[178],"obtained":[179,189],"from":[180,195],"Finally,":[184],"by":[190],"time-domain":[191],"denoising.":[192],"both":[196],"simulated":[197],"actual":[199],"field":[200],"detection":[201],"signals":[202],"show":[203],"excellent":[205],"performance":[206],"this":[208],"method.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":29},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":13}],"updated_date":"2026-07-25T15:57:00.446498","created_date":"2025-10-10T00:00:00"}
