Acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring
The invention relates to an acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring, and the method comprises the steps: extracting acoustic emission waveform feature parameters according to the actual parameter features of an acoustic emissi...
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 | JIANG LIWEI FAN SHENG JIANG JIAN HUANG KE DOU LINBIN WANG XINYU DIAO ZHIFENG |
description | The invention relates to an acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring, and the method comprises the steps: extracting acoustic emission waveform feature parameters according to the actual parameter features of an acoustic emission signal for the pressure-bearing equipment activity defect monitoring; using the extracted feature parameters as feature vectors, and defining distances between variables by using similarity coefficients; hierarchical clustering is carried out, the parameters are classified into one class one by one according to similarity coefficients among the parameters, and an acoustic emission characteristic parameter correlation hierarchical clustering tree is obtained; setting a correlation threshold, and reserving parameters with correlation coefficients below the correlation threshold as feature vectors of clustering analysis; and on the basis of determining the clustering analysis feature vector, performing K-mean clust |
format | Patent |
fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN115728396A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN115728396A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN115728396A3</originalsourceid><addsrcrecordid>eNqNyz0OgkAUBGAaC6Pe4XkACiT-lYRorKzsybIMuAn7w76H0dsLiQewmkzmm2UyFNqPLEYTrGE23hGbzqmeWigZIwhviUrLvFjI0zdUK0ZDUw8RzJNJa6hoXEcYRhMsnND8eBn5UIMWWsh6Z8TPaJ0sWtUzNr9cJdvr5VHeUgRfgYPScJCqvGfZ_rg75edDkf9jvk3bRQo</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring</title><source>esp@cenet</source><creator>JIANG LIWEI ; FAN SHENG ; JIANG JIAN ; HUANG KE ; DOU LINBIN ; WANG XINYU ; DIAO ZHIFENG</creator><creatorcontrib>JIANG LIWEI ; FAN SHENG ; JIANG JIAN ; HUANG KE ; DOU LINBIN ; WANG XINYU ; DIAO ZHIFENG</creatorcontrib><description>The invention relates to an acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring, and the method comprises the steps: extracting acoustic emission waveform feature parameters according to the actual parameter features of an acoustic emission signal for the pressure-bearing equipment activity defect monitoring; using the extracted feature parameters as feature vectors, and defining distances between variables by using similarity coefficients; hierarchical clustering is carried out, the parameters are classified into one class one by one according to similarity coefficients among the parameters, and an acoustic emission characteristic parameter correlation hierarchical clustering tree is obtained; setting a correlation threshold, and reserving parameters with correlation coefficients below the correlation threshold as feature vectors of clustering analysis; and on the basis of determining the clustering analysis feature vector, performing K-mean clust</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES ; MEASURING ; PHYSICS ; TESTING</subject><creationdate>2023</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=20230303&DB=EPODOC&CC=CN&NR=115728396A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,777,882,25545,76296</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230303&DB=EPODOC&CC=CN&NR=115728396A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>JIANG LIWEI</creatorcontrib><creatorcontrib>FAN SHENG</creatorcontrib><creatorcontrib>JIANG JIAN</creatorcontrib><creatorcontrib>HUANG KE</creatorcontrib><creatorcontrib>DOU LINBIN</creatorcontrib><creatorcontrib>WANG XINYU</creatorcontrib><creatorcontrib>DIAO ZHIFENG</creatorcontrib><title>Acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring</title><description>The invention relates to an acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring, and the method comprises the steps: extracting acoustic emission waveform feature parameters according to the actual parameter features of an acoustic emission signal for the pressure-bearing equipment activity defect monitoring; using the extracted feature parameters as feature vectors, and defining distances between variables by using similarity coefficients; hierarchical clustering is carried out, the parameters are classified into one class one by one according to similarity coefficients among the parameters, and an acoustic emission characteristic parameter correlation hierarchical clustering tree is obtained; setting a correlation threshold, and reserving parameters with correlation coefficients below the correlation threshold as feature vectors of clustering analysis; and on the basis of determining the clustering analysis feature vector, performing K-mean clust</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES</subject><subject>MEASURING</subject><subject>PHYSICS</subject><subject>TESTING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyz0OgkAUBGAaC6Pe4XkACiT-lYRorKzsybIMuAn7w76H0dsLiQewmkzmm2UyFNqPLEYTrGE23hGbzqmeWigZIwhviUrLvFjI0zdUK0ZDUw8RzJNJa6hoXEcYRhMsnND8eBn5UIMWWsh6Z8TPaJ0sWtUzNr9cJdvr5VHeUgRfgYPScJCqvGfZ_rg75edDkf9jvk3bRQo</recordid><startdate>20230303</startdate><enddate>20230303</enddate><creator>JIANG LIWEI</creator><creator>FAN SHENG</creator><creator>JIANG JIAN</creator><creator>HUANG KE</creator><creator>DOU LINBIN</creator><creator>WANG XINYU</creator><creator>DIAO ZHIFENG</creator><scope>EVB</scope></search><sort><creationdate>20230303</creationdate><title>Acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring</title><author>JIANG LIWEI ; FAN SHENG ; JIANG JIAN ; HUANG KE ; DOU LINBIN ; WANG XINYU ; DIAO ZHIFENG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN115728396A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES</topic><topic>MEASURING</topic><topic>PHYSICS</topic><topic>TESTING</topic><toplevel>online_resources</toplevel><creatorcontrib>JIANG LIWEI</creatorcontrib><creatorcontrib>FAN SHENG</creatorcontrib><creatorcontrib>JIANG JIAN</creatorcontrib><creatorcontrib>HUANG KE</creatorcontrib><creatorcontrib>DOU LINBIN</creatorcontrib><creatorcontrib>WANG XINYU</creatorcontrib><creatorcontrib>DIAO ZHIFENG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>JIANG LIWEI</au><au>FAN SHENG</au><au>JIANG JIAN</au><au>HUANG KE</au><au>DOU LINBIN</au><au>WANG XINYU</au><au>DIAO ZHIFENG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring</title><date>2023-03-03</date><risdate>2023</risdate><abstract>The invention relates to an acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring, and the method comprises the steps: extracting acoustic emission waveform feature parameters according to the actual parameter features of an acoustic emission signal for the pressure-bearing equipment activity defect monitoring; using the extracted feature parameters as feature vectors, and defining distances between variables by using similarity coefficients; hierarchical clustering is carried out, the parameters are classified into one class one by one according to similarity coefficients among the parameters, and an acoustic emission characteristic parameter correlation hierarchical clustering tree is obtained; setting a correlation threshold, and reserving parameters with correlation coefficients below the correlation threshold as feature vectors of clustering analysis; and on the basis of determining the clustering analysis feature vector, performing K-mean clust</abstract><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | |
ispartof | |
issn | |
language | chi ; eng |
recordid | cdi_epo_espacenet_CN115728396A |
source | esp@cenet |
subjects | CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES MEASURING PHYSICS TESTING |
title | Acoustic emission signal feature extraction method based on pressure-bearing equipment activity defect monitoring |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-19T01%3A07%3A05IST&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=JIANG%20LIWEI&rft.date=2023-03-03&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN115728396A%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 |