Research on Power Equipment Fault Diagnosis Technology Based on Acoustic Signal
In recent years, with the continuous growth of China’s electricity load, the power industry has developed rapidly. Power transformer is the most important and expensive in transmission and distribution system of large-scale power equipment, which undertakes the important task of power transmission....
Gespeichert in:
| Veröffentlicht in: | IOP conference series. Earth and environmental science 2021-05, Vol.769 (4), p.42099 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 4 |
| container_start_page | 42099 |
| container_title | IOP conference series. Earth and environmental science |
| container_volume | 769 |
| creator | Zou, Hongsen Chen, Haoyang Liu, Zhiyuan Wang, Guohua |
| description | In recent years, with the continuous growth of China’s electricity load, the power industry has developed rapidly. Power transformer is the most important and expensive in transmission and distribution system of large-scale power equipment, which undertakes the important task of power transmission. With the development of power system towards ultra-high voltage, large power grid and intelligence, it is particularly important to improve the safe operation level of transformers. Once the power transformer accident occurs, the repair time is longer and the influence is more serious. To solve this problem, a new power equipment fault diagnosis technology based on acoustic signals is studied in this paper, which is used to accurately diagnose and analyse the running state of the transformer. The simulation results show that the fault diagnosis based on acoustic signal is more accurate and can effectively diagnose the fault of power equipment. |
| doi_str_mv | 10.1088/1755-1315/769/4/042099 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_iop_j</sourceid><recordid>TN_cdi_proquest_journals_2528492059</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2528492059</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3709-a8c585753e1a830679c7bd9026392d73aa173e50adc80c469876aa4a8d72ca903</originalsourceid><addsrcrecordid>eNqFkF1LwzAUhoMoOKd_QQLeeFObj6ZJLufsVBAmbl6HmGZbR9d0SYvs39tSmQiCV-fAed6XwwPANUZ3GAkRY85YhClmMU9lnMQoIUjKEzA6Hk6PO-Ln4CKELUIpT6gcgfmbDVZ7s4Gugq_u03qY7dui3tmqgTPdlg18KPS6cqEIcGnNpnKlWx_gvQ427zMT49rQFAYuinWly0twttJlsFffcwzeZ9ly-hS9zB-fp5OXyFCOZKSFYYJxRi3WgnbPSMM_colISiXJOdUac2oZ0rkRyCSpFDzVOtEi58RoiegY3Ay9tXf71oZGbV3ruweCIoyIRBLEZEelA2W8C8Hblap9sdP-oDBSvTzVe1G9I9XJU4ka5HXB2yFYuPqnOcsWvzBV56sOJX-g__R_Aa1-fJ4</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2528492059</pqid></control><display><type>article</type><title>Research on Power Equipment Fault Diagnosis Technology Based on Acoustic Signal</title><source>IOP Publishing Free Content</source><source>EZB-FREE-00999 freely available EZB journals</source><source>IOPscience extra</source><creator>Zou, Hongsen ; Chen, Haoyang ; Liu, Zhiyuan ; Wang, Guohua</creator><creatorcontrib>Zou, Hongsen ; Chen, Haoyang ; Liu, Zhiyuan ; Wang, Guohua</creatorcontrib><description>In recent years, with the continuous growth of China’s electricity load, the power industry has developed rapidly. Power transformer is the most important and expensive in transmission and distribution system of large-scale power equipment, which undertakes the important task of power transmission. With the development of power system towards ultra-high voltage, large power grid and intelligence, it is particularly important to improve the safe operation level of transformers. Once the power transformer accident occurs, the repair time is longer and the influence is more serious. To solve this problem, a new power equipment fault diagnosis technology based on acoustic signals is studied in this paper, which is used to accurately diagnose and analyse the running state of the transformer. The simulation results show that the fault diagnosis based on acoustic signal is more accurate and can effectively diagnose the fault of power equipment.</description><identifier>ISSN: 1755-1307</identifier><identifier>EISSN: 1755-1315</identifier><identifier>DOI: 10.1088/1755-1315/769/4/042099</identifier><language>eng</language><publisher>Bristol: IOP Publishing</publisher><subject>Acoustics ; Electric industries ; Electric power distribution ; Electric power grids ; Electric power systems ; Electricity distribution ; Fault diagnosis ; High voltage ; Industrial development ; Intelligence ; Repair time ; Technology ; Transformers</subject><ispartof>IOP conference series. Earth and environmental science, 2021-05, Vol.769 (4), p.42099</ispartof><rights>Published under licence by IOP Publishing Ltd</rights><rights>2021. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3709-a8c585753e1a830679c7bd9026392d73aa173e50adc80c469876aa4a8d72ca903</citedby><cites>FETCH-LOGICAL-c3709-a8c585753e1a830679c7bd9026392d73aa173e50adc80c469876aa4a8d72ca903</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1755-1315/769/4/042099/pdf$$EPDF$$P50$$Giop$$Hfree_for_read</linktopdf><link.rule.ids>314,780,784,27922,27923,38866,38888,53838,53865</link.rule.ids></links><search><creatorcontrib>Zou, Hongsen</creatorcontrib><creatorcontrib>Chen, Haoyang</creatorcontrib><creatorcontrib>Liu, Zhiyuan</creatorcontrib><creatorcontrib>Wang, Guohua</creatorcontrib><title>Research on Power Equipment Fault Diagnosis Technology Based on Acoustic Signal</title><title>IOP conference series. Earth and environmental science</title><addtitle>IOP Conf. Ser.: Earth Environ. Sci</addtitle><description>In recent years, with the continuous growth of China’s electricity load, the power industry has developed rapidly. Power transformer is the most important and expensive in transmission and distribution system of large-scale power equipment, which undertakes the important task of power transmission. With the development of power system towards ultra-high voltage, large power grid and intelligence, it is particularly important to improve the safe operation level of transformers. Once the power transformer accident occurs, the repair time is longer and the influence is more serious. To solve this problem, a new power equipment fault diagnosis technology based on acoustic signals is studied in this paper, which is used to accurately diagnose and analyse the running state of the transformer. The simulation results show that the fault diagnosis based on acoustic signal is more accurate and can effectively diagnose the fault of power equipment.</description><subject>Acoustics</subject><subject>Electric industries</subject><subject>Electric power distribution</subject><subject>Electric power grids</subject><subject>Electric power systems</subject><subject>Electricity distribution</subject><subject>Fault diagnosis</subject><subject>High voltage</subject><subject>Industrial development</subject><subject>Intelligence</subject><subject>Repair time</subject><subject>Technology</subject><subject>Transformers</subject><issn>1755-1307</issn><issn>1755-1315</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>O3W</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkF1LwzAUhoMoOKd_QQLeeFObj6ZJLufsVBAmbl6HmGZbR9d0SYvs39tSmQiCV-fAed6XwwPANUZ3GAkRY85YhClmMU9lnMQoIUjKEzA6Hk6PO-Ln4CKELUIpT6gcgfmbDVZ7s4Gugq_u03qY7dui3tmqgTPdlg18KPS6cqEIcGnNpnKlWx_gvQ427zMT49rQFAYuinWly0twttJlsFffcwzeZ9ly-hS9zB-fp5OXyFCOZKSFYYJxRi3WgnbPSMM_colISiXJOdUac2oZ0rkRyCSpFDzVOtEi58RoiegY3Ay9tXf71oZGbV3ruweCIoyIRBLEZEelA2W8C8Hblap9sdP-oDBSvTzVe1G9I9XJU4ka5HXB2yFYuPqnOcsWvzBV56sOJX-g__R_Aa1-fJ4</recordid><startdate>20210501</startdate><enddate>20210501</enddate><creator>Zou, Hongsen</creator><creator>Chen, Haoyang</creator><creator>Liu, Zhiyuan</creator><creator>Wang, Guohua</creator><general>IOP Publishing</general><scope>O3W</scope><scope>TSCCA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope></search><sort><creationdate>20210501</creationdate><title>Research on Power Equipment Fault Diagnosis Technology Based on Acoustic Signal</title><author>Zou, Hongsen ; Chen, Haoyang ; Liu, Zhiyuan ; Wang, Guohua</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3709-a8c585753e1a830679c7bd9026392d73aa173e50adc80c469876aa4a8d72ca903</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Acoustics</topic><topic>Electric industries</topic><topic>Electric power distribution</topic><topic>Electric power grids</topic><topic>Electric power systems</topic><topic>Electricity distribution</topic><topic>Fault diagnosis</topic><topic>High voltage</topic><topic>Industrial development</topic><topic>Intelligence</topic><topic>Repair time</topic><topic>Technology</topic><topic>Transformers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zou, Hongsen</creatorcontrib><creatorcontrib>Chen, Haoyang</creatorcontrib><creatorcontrib>Liu, Zhiyuan</creatorcontrib><creatorcontrib>Wang, Guohua</creatorcontrib><collection>IOP Publishing Free Content</collection><collection>IOPscience (Open Access)</collection><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Environmental Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Environmental Science Collection</collection><jtitle>IOP conference series. Earth and environmental science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zou, Hongsen</au><au>Chen, Haoyang</au><au>Liu, Zhiyuan</au><au>Wang, Guohua</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Research on Power Equipment Fault Diagnosis Technology Based on Acoustic Signal</atitle><jtitle>IOP conference series. Earth and environmental science</jtitle><addtitle>IOP Conf. Ser.: Earth Environ. Sci</addtitle><date>2021-05-01</date><risdate>2021</risdate><volume>769</volume><issue>4</issue><spage>42099</spage><pages>42099-</pages><issn>1755-1307</issn><eissn>1755-1315</eissn><abstract>In recent years, with the continuous growth of China’s electricity load, the power industry has developed rapidly. Power transformer is the most important and expensive in transmission and distribution system of large-scale power equipment, which undertakes the important task of power transmission. With the development of power system towards ultra-high voltage, large power grid and intelligence, it is particularly important to improve the safe operation level of transformers. Once the power transformer accident occurs, the repair time is longer and the influence is more serious. To solve this problem, a new power equipment fault diagnosis technology based on acoustic signals is studied in this paper, which is used to accurately diagnose and analyse the running state of the transformer. The simulation results show that the fault diagnosis based on acoustic signal is more accurate and can effectively diagnose the fault of power equipment.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1755-1315/769/4/042099</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1755-1307 |
| ispartof | IOP conference series. Earth and environmental science, 2021-05, Vol.769 (4), p.42099 |
| issn | 1755-1307 1755-1315 |
| language | eng |
| recordid | cdi_proquest_journals_2528492059 |
| source | IOP Publishing Free Content; EZB-FREE-00999 freely available EZB journals; IOPscience extra |
| subjects | Acoustics Electric industries Electric power distribution Electric power grids Electric power systems Electricity distribution Fault diagnosis High voltage Industrial development Intelligence Repair time Technology Transformers |
| title | Research on Power Equipment Fault Diagnosis Technology Based on Acoustic Signal |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T20%3A29%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_iop_j&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Research%20on%20Power%20Equipment%20Fault%20Diagnosis%20Technology%20Based%20on%20Acoustic%20Signal&rft.jtitle=IOP%20conference%20series.%20Earth%20and%20environmental%20science&rft.au=Zou,%20Hongsen&rft.date=2021-05-01&rft.volume=769&rft.issue=4&rft.spage=42099&rft.pages=42099-&rft.issn=1755-1307&rft.eissn=1755-1315&rft_id=info:doi/10.1088/1755-1315/769/4/042099&rft_dat=%3Cproquest_iop_j%3E2528492059%3C/proquest_iop_j%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2528492059&rft_id=info:pmid/&rfr_iscdi=true |