GIS partial discharge fault detection method based on improved wavelet threshold denoising
The invention discloses a GIS partial discharge fault detection method based on improved wavelet threshold denoising. The method of the invention comprises the following steps of: performing wavelet transform on data detected by an ultrahigh frequency sensor, and performing 4 level decomposition on...
Gespeichert in:
| Hauptverfasser: | , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Patent |
| Sprache: | chi ; eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | LIU JIANGMING SUN ZHENGZHU HUANG JILAI XIA XIAOBO WU XUYANG MAO YONGMING ZHOU XUN SHENG JUN WANG ZHENYI ZHU LIANG MA TAO XU CHONG WU ZUNDONG WANG YIFAN DU YUN RAO HAIWEI GONG JINLONG LOU GANG |
| description | The invention discloses a GIS partial discharge fault detection method based on improved wavelet threshold denoising. The method of the invention comprises the following steps of: performing wavelet transform on data detected by an ultrahigh frequency sensor, and performing 4 level decomposition on detection data of the sensor by using a dB4 mother wavelet to obtain wavelet coefficients at different scales; after the wavelet decomposition coefficient threshold is quantized and the threshold is selected, removing the wavelet coefficients smaller than the threshold, and performing threshold function process on wavelet coefficients larger than the threshold, thereby obtaining each level coefficients after the threshold function process; and performing signal reconstruction on each wavelet level coefficient by wavelet inverse transform to realize wavelet denoising. Compared with a traditional soft and hard threshold denoising algorithm, the GIS partial discharge fault detection method based on the improved wavele |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN109557429A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN109557429A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN109557429A3</originalsourceid><addsrcrecordid>eNqNizsOwjAQBdNQIOAOywGQ-EVRShTxa2igoomW-CW25NiWvYTrk4IDUL0Zad40e56vdwocxbAlZVKjOXaglt9WSEHQiPGOeoj2il6coGh004foh5E_PMBCSHRE0t6q8eS8ScZ182zSsk1Y_HaWLU_HR3VZIfgaKXADB6mr22Zd5nmx35aH3T_NFyc7O1I</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>GIS partial discharge fault detection method based on improved wavelet threshold denoising</title><source>esp@cenet</source><creator>LIU JIANGMING ; SUN ZHENGZHU ; HUANG JILAI ; XIA XIAOBO ; WU XUYANG ; MAO YONGMING ; ZHOU XUN ; SHENG JUN ; WANG ZHENYI ; ZHU LIANG ; MA TAO ; XU CHONG ; WU ZUNDONG ; WANG YIFAN ; DU YUN ; RAO HAIWEI ; GONG JINLONG ; LOU GANG</creator><creatorcontrib>LIU JIANGMING ; SUN ZHENGZHU ; HUANG JILAI ; XIA XIAOBO ; WU XUYANG ; MAO YONGMING ; ZHOU XUN ; SHENG JUN ; WANG ZHENYI ; ZHU LIANG ; MA TAO ; XU CHONG ; WU ZUNDONG ; WANG YIFAN ; DU YUN ; RAO HAIWEI ; GONG JINLONG ; LOU GANG</creatorcontrib><description>The invention discloses a GIS partial discharge fault detection method based on improved wavelet threshold denoising. The method of the invention comprises the following steps of: performing wavelet transform on data detected by an ultrahigh frequency sensor, and performing 4 level decomposition on detection data of the sensor by using a dB4 mother wavelet to obtain wavelet coefficients at different scales; after the wavelet decomposition coefficient threshold is quantized and the threshold is selected, removing the wavelet coefficients smaller than the threshold, and performing threshold function process on wavelet coefficients larger than the threshold, thereby obtaining each level coefficients after the threshold function process; and performing signal reconstruction on each wavelet level coefficient by wavelet inverse transform to realize wavelet denoising. Compared with a traditional soft and hard threshold denoising algorithm, the GIS partial discharge fault detection method based on the improved wavele</description><language>chi ; eng</language><subject>MEASURING ; MEASURING ELECTRIC VARIABLES ; MEASURING MAGNETIC VARIABLES ; PHYSICS ; TESTING</subject><creationdate>2019</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20190402&DB=EPODOC&CC=CN&NR=109557429A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,777,882,25545,76296</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20190402&DB=EPODOC&CC=CN&NR=109557429A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LIU JIANGMING</creatorcontrib><creatorcontrib>SUN ZHENGZHU</creatorcontrib><creatorcontrib>HUANG JILAI</creatorcontrib><creatorcontrib>XIA XIAOBO</creatorcontrib><creatorcontrib>WU XUYANG</creatorcontrib><creatorcontrib>MAO YONGMING</creatorcontrib><creatorcontrib>ZHOU XUN</creatorcontrib><creatorcontrib>SHENG JUN</creatorcontrib><creatorcontrib>WANG ZHENYI</creatorcontrib><creatorcontrib>ZHU LIANG</creatorcontrib><creatorcontrib>MA TAO</creatorcontrib><creatorcontrib>XU CHONG</creatorcontrib><creatorcontrib>WU ZUNDONG</creatorcontrib><creatorcontrib>WANG YIFAN</creatorcontrib><creatorcontrib>DU YUN</creatorcontrib><creatorcontrib>RAO HAIWEI</creatorcontrib><creatorcontrib>GONG JINLONG</creatorcontrib><creatorcontrib>LOU GANG</creatorcontrib><title>GIS partial discharge fault detection method based on improved wavelet threshold denoising</title><description>The invention discloses a GIS partial discharge fault detection method based on improved wavelet threshold denoising. The method of the invention comprises the following steps of: performing wavelet transform on data detected by an ultrahigh frequency sensor, and performing 4 level decomposition on detection data of the sensor by using a dB4 mother wavelet to obtain wavelet coefficients at different scales; after the wavelet decomposition coefficient threshold is quantized and the threshold is selected, removing the wavelet coefficients smaller than the threshold, and performing threshold function process on wavelet coefficients larger than the threshold, thereby obtaining each level coefficients after the threshold function process; and performing signal reconstruction on each wavelet level coefficient by wavelet inverse transform to realize wavelet denoising. Compared with a traditional soft and hard threshold denoising algorithm, the GIS partial discharge fault detection method based on the improved wavele</description><subject>MEASURING</subject><subject>MEASURING ELECTRIC VARIABLES</subject><subject>MEASURING MAGNETIC VARIABLES</subject><subject>PHYSICS</subject><subject>TESTING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2019</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNizsOwjAQBdNQIOAOywGQ-EVRShTxa2igoomW-CW25NiWvYTrk4IDUL0Zad40e56vdwocxbAlZVKjOXaglt9WSEHQiPGOeoj2il6coGh004foh5E_PMBCSHRE0t6q8eS8ScZ182zSsk1Y_HaWLU_HR3VZIfgaKXADB6mr22Zd5nmx35aH3T_NFyc7O1I</recordid><startdate>20190402</startdate><enddate>20190402</enddate><creator>LIU JIANGMING</creator><creator>SUN ZHENGZHU</creator><creator>HUANG JILAI</creator><creator>XIA XIAOBO</creator><creator>WU XUYANG</creator><creator>MAO YONGMING</creator><creator>ZHOU XUN</creator><creator>SHENG JUN</creator><creator>WANG ZHENYI</creator><creator>ZHU LIANG</creator><creator>MA TAO</creator><creator>XU CHONG</creator><creator>WU ZUNDONG</creator><creator>WANG YIFAN</creator><creator>DU YUN</creator><creator>RAO HAIWEI</creator><creator>GONG JINLONG</creator><creator>LOU GANG</creator><scope>EVB</scope></search><sort><creationdate>20190402</creationdate><title>GIS partial discharge fault detection method based on improved wavelet threshold denoising</title><author>LIU JIANGMING ; SUN ZHENGZHU ; HUANG JILAI ; XIA XIAOBO ; WU XUYANG ; MAO YONGMING ; ZHOU XUN ; SHENG JUN ; WANG ZHENYI ; ZHU LIANG ; MA TAO ; XU CHONG ; WU ZUNDONG ; WANG YIFAN ; DU YUN ; RAO HAIWEI ; GONG JINLONG ; LOU GANG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN109557429A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2019</creationdate><topic>MEASURING</topic><topic>MEASURING ELECTRIC VARIABLES</topic><topic>MEASURING MAGNETIC VARIABLES</topic><topic>PHYSICS</topic><topic>TESTING</topic><toplevel>online_resources</toplevel><creatorcontrib>LIU JIANGMING</creatorcontrib><creatorcontrib>SUN ZHENGZHU</creatorcontrib><creatorcontrib>HUANG JILAI</creatorcontrib><creatorcontrib>XIA XIAOBO</creatorcontrib><creatorcontrib>WU XUYANG</creatorcontrib><creatorcontrib>MAO YONGMING</creatorcontrib><creatorcontrib>ZHOU XUN</creatorcontrib><creatorcontrib>SHENG JUN</creatorcontrib><creatorcontrib>WANG ZHENYI</creatorcontrib><creatorcontrib>ZHU LIANG</creatorcontrib><creatorcontrib>MA TAO</creatorcontrib><creatorcontrib>XU CHONG</creatorcontrib><creatorcontrib>WU ZUNDONG</creatorcontrib><creatorcontrib>WANG YIFAN</creatorcontrib><creatorcontrib>DU YUN</creatorcontrib><creatorcontrib>RAO HAIWEI</creatorcontrib><creatorcontrib>GONG JINLONG</creatorcontrib><creatorcontrib>LOU GANG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LIU JIANGMING</au><au>SUN ZHENGZHU</au><au>HUANG JILAI</au><au>XIA XIAOBO</au><au>WU XUYANG</au><au>MAO YONGMING</au><au>ZHOU XUN</au><au>SHENG JUN</au><au>WANG ZHENYI</au><au>ZHU LIANG</au><au>MA TAO</au><au>XU CHONG</au><au>WU ZUNDONG</au><au>WANG YIFAN</au><au>DU YUN</au><au>RAO HAIWEI</au><au>GONG JINLONG</au><au>LOU GANG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>GIS partial discharge fault detection method based on improved wavelet threshold denoising</title><date>2019-04-02</date><risdate>2019</risdate><abstract>The invention discloses a GIS partial discharge fault detection method based on improved wavelet threshold denoising. The method of the invention comprises the following steps of: performing wavelet transform on data detected by an ultrahigh frequency sensor, and performing 4 level decomposition on detection data of the sensor by using a dB4 mother wavelet to obtain wavelet coefficients at different scales; after the wavelet decomposition coefficient threshold is quantized and the threshold is selected, removing the wavelet coefficients smaller than the threshold, and performing threshold function process on wavelet coefficients larger than the threshold, thereby obtaining each level coefficients after the threshold function process; and performing signal reconstruction on each wavelet level coefficient by wavelet inverse transform to realize wavelet denoising. Compared with a traditional soft and hard threshold denoising algorithm, the GIS partial discharge fault detection method based on the improved wavele</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | chi ; eng |
| recordid | cdi_epo_espacenet_CN109557429A |
| source | esp@cenet |
| subjects | MEASURING MEASURING ELECTRIC VARIABLES MEASURING MAGNETIC VARIABLES PHYSICS TESTING |
| title | GIS partial discharge fault detection method based on improved wavelet threshold denoising |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T13%3A57%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=LIU%20JIANGMING&rft.date=2019-04-02&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN109557429A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |