Vibration-based robust health diagnostics for mechanical failure modes of power transformers
A power transformer is one of the main components in a power plant and transformer failure may provoke power plant shut-down with significant capital loss. Many techniques of vibration-based health diagnostics have been developed in order to prevent mechanical failures of the transformer. Vibration-...
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| creator | Joung Taek Yoon Youn, Byeng D. Kyung Min Park Wook-Ryun Lee |
| description | A power transformer is one of the main components in a power plant and transformer failure may provoke power plant shut-down with significant capital loss. Many techniques of vibration-based health diagnostics have been developed in order to prevent mechanical failures of the transformer. Vibration-based health diagnostics results are generally sensitive to the number of sensors and their locations. This study aims at developing robust health diagnostics for two dominant mechanical failure mechanisms of the transformer. Based upon the characteristics of transformer vibration, robust health indices were developed using sensitivity analysis. This study employed 33 transformers and each with 36~48 accelerometers for demonstration purpose. It is concluded that the proposed health index are suitable for robust health diagnostics and fault identification of power transformers. |
| doi_str_mv | 10.1109/ICPHM.2013.6621421 |
| format | Conference Proceeding |
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Many techniques of vibration-based health diagnostics have been developed in order to prevent mechanical failures of the transformer. Vibration-based health diagnostics results are generally sensitive to the number of sensors and their locations. This study aims at developing robust health diagnostics for two dominant mechanical failure mechanisms of the transformer. Based upon the characteristics of transformer vibration, robust health indices were developed using sensitivity analysis. This study employed 33 transformers and each with 36~48 accelerometers for demonstration purpose. It is concluded that the proposed health index are suitable for robust health diagnostics and fault identification of power transformers.</description><identifier>EISBN: 1467357227</identifier><identifier>EISBN: 9781467357234</identifier><identifier>EISBN: 1467357235</identifier><identifier>EISBN: 9781467357227</identifier><identifier>DOI: 10.1109/ICPHM.2013.6621421</identifier><language>eng</language><publisher>IEEE</publisher><subject>Fault diagnosis ; fault identification ; health index ; Monitoring ; Nickel ; oil-filled power transformer ; sensitivity analysis ; Windings</subject><ispartof>2013 IEEE Conference on Prognostics and Health Management (PHM), 2013, p.1-5</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6621421$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6621421$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Joung Taek Yoon</creatorcontrib><creatorcontrib>Youn, Byeng D.</creatorcontrib><creatorcontrib>Kyung Min Park</creatorcontrib><creatorcontrib>Wook-Ryun Lee</creatorcontrib><title>Vibration-based robust health diagnostics for mechanical failure modes of power transformers</title><title>2013 IEEE Conference on Prognostics and Health Management (PHM)</title><addtitle>ICPHM</addtitle><description>A power transformer is one of the main components in a power plant and transformer failure may provoke power plant shut-down with significant capital loss. Many techniques of vibration-based health diagnostics have been developed in order to prevent mechanical failures of the transformer. Vibration-based health diagnostics results are generally sensitive to the number of sensors and their locations. This study aims at developing robust health diagnostics for two dominant mechanical failure mechanisms of the transformer. Based upon the characteristics of transformer vibration, robust health indices were developed using sensitivity analysis. This study employed 33 transformers and each with 36~48 accelerometers for demonstration purpose. It is concluded that the proposed health index are suitable for robust health diagnostics and fault identification of power transformers.</description><subject>Fault diagnosis</subject><subject>fault identification</subject><subject>health index</subject><subject>Monitoring</subject><subject>Nickel</subject><subject>oil-filled power transformer</subject><subject>sensitivity analysis</subject><subject>Windings</subject><isbn>1467357227</isbn><isbn>9781467357234</isbn><isbn>1467357235</isbn><isbn>9781467357227</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj81KxDAURuNCUMd5Ad3kBVrz06TNUoo6AyO6GFwJQ256YyNtMyQdxLe34KzO5jsfHELuOCs5Z-Zh275vXkvBuCy1FrwS_ILc8ErXUtVC1FdknfM3Y4zXWisprsnnR4Bk5xCnAmzGjqYIpzzTHu0w97QL9muKeQ4uUx8THdH1dgrODtTbMJwS0jF2mGn09Bh_MNE52Skv0xFTviWX3g4Z12euyP75ad9uit3by7Z93BXBsLnwzivLdQVSmBqgahQ4D6jRy4XWSTCuQQ5ONQDKGA2V8V64SntVq0Vbkfv_24CIh2MKo02_h3O__APJ2VR-</recordid><startdate>201306</startdate><enddate>201306</enddate><creator>Joung Taek Yoon</creator><creator>Youn, Byeng D.</creator><creator>Kyung Min Park</creator><creator>Wook-Ryun Lee</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201306</creationdate><title>Vibration-based robust health diagnostics for mechanical failure modes of power transformers</title><author>Joung Taek Yoon ; Youn, Byeng D. ; Kyung Min Park ; Wook-Ryun Lee</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-fcf5a164b3297bb485bcfbe6ef3cfbac3b9c8e1bc58bb5996b49ff2c46f5754b3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Fault diagnosis</topic><topic>fault identification</topic><topic>health index</topic><topic>Monitoring</topic><topic>Nickel</topic><topic>oil-filled power transformer</topic><topic>sensitivity analysis</topic><topic>Windings</topic><toplevel>online_resources</toplevel><creatorcontrib>Joung Taek Yoon</creatorcontrib><creatorcontrib>Youn, Byeng D.</creatorcontrib><creatorcontrib>Kyung Min Park</creatorcontrib><creatorcontrib>Wook-Ryun Lee</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Joung Taek Yoon</au><au>Youn, Byeng D.</au><au>Kyung Min Park</au><au>Wook-Ryun Lee</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Vibration-based robust health diagnostics for mechanical failure modes of power transformers</atitle><btitle>2013 IEEE Conference on Prognostics and Health Management (PHM)</btitle><stitle>ICPHM</stitle><date>2013-06</date><risdate>2013</risdate><spage>1</spage><epage>5</epage><pages>1-5</pages><eisbn>1467357227</eisbn><eisbn>9781467357234</eisbn><eisbn>1467357235</eisbn><eisbn>9781467357227</eisbn><abstract>A power transformer is one of the main components in a power plant and transformer failure may provoke power plant shut-down with significant capital loss. Many techniques of vibration-based health diagnostics have been developed in order to prevent mechanical failures of the transformer. Vibration-based health diagnostics results are generally sensitive to the number of sensors and their locations. This study aims at developing robust health diagnostics for two dominant mechanical failure mechanisms of the transformer. Based upon the characteristics of transformer vibration, robust health indices were developed using sensitivity analysis. This study employed 33 transformers and each with 36~48 accelerometers for demonstration purpose. It is concluded that the proposed health index are suitable for robust health diagnostics and fault identification of power transformers.</abstract><pub>IEEE</pub><doi>10.1109/ICPHM.2013.6621421</doi><tpages>5</tpages></addata></record> |
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| subjects | Fault diagnosis fault identification health index Monitoring Nickel oil-filled power transformer sensitivity analysis Windings |
| title | Vibration-based robust health diagnostics for mechanical failure modes of power transformers |
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