Development, application and evaluation of a computational tool for management high voltage break disconnector based on self-organizing maps and image processing
This work has the objective of developing, analysing and applying a new tool for management the status of break disconnectors in high voltage substations from digital images. This tool uses a non-supervised kind of artificial neural network using the Kohonen learning algorithm, known as a self-organ...
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| Veröffentlicht in: | Energy conversion and management 2010-11, Vol.51 (11), p.2279-2284 |
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| container_title | Energy conversion and management |
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| creator | Colaço, Daniel Freitas de Alexandria, Auzuir R. Cortez, Paulo César Frota, João Batista B. Lima, José Nunes de de Albuquerque, Victor Hugo C. |
| description | This work has the objective of developing, analysing and applying a new tool for management the status of break disconnectors in high voltage substations from digital images. This tool uses a non-supervised kind of artificial neural network using the Kohonen learning algorithm, known as a self-organizing maps. In order to develop the proposed tool, C/C++ programming language, provided with easily used interfaces, is used. In order to obtain the results, three environments are considered: one for laboratory simulation and two pilot projects installed in the Fortaleza II/CHESF substation. These pilots are used for 230
kV EV-2000 type and 500
kV semi-pantographic type break disconnector management tests. The results prove the developed system’s efficiency, because it is able to detect 100% of open and closed identification situations. However, the neural network utilised for management break disconnectors has become suitable for installation in high voltage substations in order to support the maintenance team in safely handling these disconnectors. |
| doi_str_mv | 10.1016/j.enconman.2010.03.023 |
| format | Article |
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kV EV-2000 type and 500
kV semi-pantographic type break disconnector management tests. The results prove the developed system’s efficiency, because it is able to detect 100% of open and closed identification situations. However, the neural network utilised for management break disconnectors has become suitable for installation in high voltage substations in order to support the maintenance team in safely handling these disconnectors.</description><identifier>ISSN: 0196-8904</identifier><identifier>EISSN: 1879-2227</identifier><identifier>DOI: 10.1016/j.enconman.2010.03.023</identifier><identifier>CODEN: ECMADL</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Applied sciences ; Break disconnectors ; Breaking ; Computer simulation ; Disengaging ; Electrical engineering. Electrical power engineering ; Electrical power engineering ; Exact sciences and technology ; High voltages ; Maintenance ; Management ; Power networks and lines ; SOM artificial neural network ; Substations</subject><ispartof>Energy conversion and management, 2010-11, Vol.51 (11), p.2279-2284</ispartof><rights>2010 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c407t-3a353b200bc0bf320fdeb05cd254e95ea24ff96d10b12fed44379563ff10033f3</citedby><cites>FETCH-LOGICAL-c407t-3a353b200bc0bf320fdeb05cd254e95ea24ff96d10b12fed44379563ff10033f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.enconman.2010.03.023$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,778,782,3539,27907,27908,45978</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=22996704$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Colaço, Daniel Freitas</creatorcontrib><creatorcontrib>de Alexandria, Auzuir R.</creatorcontrib><creatorcontrib>Cortez, Paulo César</creatorcontrib><creatorcontrib>Frota, João Batista B.</creatorcontrib><creatorcontrib>Lima, José Nunes de</creatorcontrib><creatorcontrib>de Albuquerque, Victor Hugo C.</creatorcontrib><title>Development, application and evaluation of a computational tool for management high voltage break disconnector based on self-organizing maps and image processing</title><title>Energy conversion and management</title><description>This work has the objective of developing, analysing and applying a new tool for management the status of break disconnectors in high voltage substations from digital images. This tool uses a non-supervised kind of artificial neural network using the Kohonen learning algorithm, known as a self-organizing maps. In order to develop the proposed tool, C/C++ programming language, provided with easily used interfaces, is used. In order to obtain the results, three environments are considered: one for laboratory simulation and two pilot projects installed in the Fortaleza II/CHESF substation. These pilots are used for 230
kV EV-2000 type and 500
kV semi-pantographic type break disconnector management tests. The results prove the developed system’s efficiency, because it is able to detect 100% of open and closed identification situations. However, the neural network utilised for management break disconnectors has become suitable for installation in high voltage substations in order to support the maintenance team in safely handling these disconnectors.</description><subject>Applied sciences</subject><subject>Break disconnectors</subject><subject>Breaking</subject><subject>Computer simulation</subject><subject>Disengaging</subject><subject>Electrical engineering. Electrical power engineering</subject><subject>Electrical power engineering</subject><subject>Exact sciences and technology</subject><subject>High voltages</subject><subject>Maintenance</subject><subject>Management</subject><subject>Power networks and lines</subject><subject>SOM artificial neural network</subject><subject>Substations</subject><issn>0196-8904</issn><issn>1879-2227</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNqFkcFu1DAQhiMEEkvhFZAvCA5kGduJk9xAhRakSlzgbDnOeOvFsYOdXQnehjdltls4wsny-Jv_H89fVc85bDlw9Wa_xWhTnE3cCqAiyC0I-aDa8L4baiFE97DaAB9U3Q_QPK6elLIHANmC2lS_3uMRQ1pmjOtrZpYleGtWnyIzcWJ4NOFwvibHDLNpXg7rXcEEtqYUmEuZkbXZ4UmC3frdLTumsFKBjRnNNzb5QuNFtCuhoyk4MdIrGFyd8s5E_9PHHWks5c7Tz6fWJSeLpdDL0-qRM6Hgs_vzovp69eHL5cf65vP1p8t3N7VtoFtraWQrRwEwWhidFOAmHKG1k2gbHFo0onFuUBOHkQuHU9PIbmiVdI7TLqSTF9XLsy5Zfz9gWfVMg2MIJmI6FN21UvWqh4HIV_8kueq4lNC3glB1Rm1OpWR0esn0wfxDc9Cn9PRe_0lPn9LTIDWlR40v7j1MsSa4bKL15W-3EMOgOmiIe3vmkFZz9Jh1sZ4UcfKZNq6n5P9n9RvlObd3</recordid><startdate>20101101</startdate><enddate>20101101</enddate><creator>Colaço, Daniel Freitas</creator><creator>de Alexandria, Auzuir R.</creator><creator>Cortez, Paulo César</creator><creator>Frota, João Batista B.</creator><creator>Lima, José Nunes de</creator><creator>de Albuquerque, Victor Hugo C.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>7ST</scope><scope>C1K</scope><scope>SOI</scope></search><sort><creationdate>20101101</creationdate><title>Development, application and evaluation of a computational tool for management high voltage break disconnector based on self-organizing maps and image processing</title><author>Colaço, Daniel Freitas ; de Alexandria, Auzuir R. ; Cortez, Paulo César ; Frota, João Batista B. ; Lima, José Nunes de ; de Albuquerque, Victor Hugo C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c407t-3a353b200bc0bf320fdeb05cd254e95ea24ff96d10b12fed44379563ff10033f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Applied sciences</topic><topic>Break disconnectors</topic><topic>Breaking</topic><topic>Computer simulation</topic><topic>Disengaging</topic><topic>Electrical engineering. 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kV EV-2000 type and 500
kV semi-pantographic type break disconnector management tests. The results prove the developed system’s efficiency, because it is able to detect 100% of open and closed identification situations. However, the neural network utilised for management break disconnectors has become suitable for installation in high voltage substations in order to support the maintenance team in safely handling these disconnectors.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.enconman.2010.03.023</doi><tpages>6</tpages></addata></record> |
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| ispartof | Energy conversion and management, 2010-11, Vol.51 (11), p.2279-2284 |
| issn | 0196-8904 1879-2227 |
| language | eng |
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| source | Elsevier ScienceDirect Journals |
| subjects | Applied sciences Break disconnectors Breaking Computer simulation Disengaging Electrical engineering. Electrical power engineering Electrical power engineering Exact sciences and technology High voltages Maintenance Management Power networks and lines SOM artificial neural network Substations |
| title | Development, application and evaluation of a computational tool for management high voltage break disconnector based on self-organizing maps and image processing |
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