A Method for Online Stator Insulation Prognosis for Inverter-Driven Machines
A significant portion of faults experienced by electrical machines is caused by degraded insulation. In order to reduce the effects of a failure, it is important to monitor the health of the insulation, preferably while the machine continues operation without any expensive equipment. In this paper,...
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| Veröffentlicht in: | IEEE transactions on industry applications 2018-11, Vol.54 (6), p.5897-5906 |
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| container_title | IEEE transactions on industry applications |
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| creator | Jensen, William R. Strangas, Elias G. Foster, Shanelle N. |
| description | A significant portion of faults experienced by electrical machines is caused by degraded insulation. In order to reduce the effects of a failure, it is important to monitor the health of the insulation, preferably while the machine continues operation without any expensive equipment. In this paper, an online method to calculate the remaining useful lifetime (RUL) of the stator insulation with a simple equipment is proposed. The accelerated degradation testing was performed by exposing the stator of an electric machine to high temperatures. An extended Kalman filter algorithm is developed to calculate the RUL. A simple analog circuit is used to show how lower sampling rates can be used to capture the necessary information for prognosis. With this circuit, the same trend used to provide a prognosis for the insulation can be measured online without using any expensive or special technology. |
| doi_str_mv | 10.1109/TIA.2018.2854408 |
| format | Article |
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In order to reduce the effects of a failure, it is important to monitor the health of the insulation, preferably while the machine continues operation without any expensive equipment. In this paper, an online method to calculate the remaining useful lifetime (RUL) of the stator insulation with a simple equipment is proposed. The accelerated degradation testing was performed by exposing the stator of an electric machine to high temperatures. An extended Kalman filter algorithm is developed to calculate the RUL. A simple analog circuit is used to show how lower sampling rates can be used to capture the necessary information for prognosis. With this circuit, the same trend used to provide a prognosis for the insulation can be measured online without using any expensive or special technology.</description><identifier>ISSN: 0093-9994</identifier><identifier>EISSN: 1939-9367</identifier><identifier>DOI: 10.1109/TIA.2018.2854408</identifier><identifier>CODEN: ITIACR</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Accelerated tests ; Analog circuits ; Capacitance ; Current measurement ; Degradation ; Electrical machines ; Extended Kalman filter ; extended Kalman filter (EKF) ; fault prognosis ; Insulation ; leakage current ; Leakage currents ; Mathematical analysis ; Prognosis ; Prognostics and health management ; Stators</subject><ispartof>IEEE transactions on industry applications, 2018-11, Vol.54 (6), p.5897-5906</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c357t-65125a1036ac989cf19139d72439ef87276fb8cdd2d8d92a2110ca77acd6ac003</citedby><cites>FETCH-LOGICAL-c357t-65125a1036ac989cf19139d72439ef87276fb8cdd2d8d92a2110ca77acd6ac003</cites><orcidid>0000-0003-4699-3493 ; 0000-0001-9630-5500</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8408756$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,777,781,793,27905,27906,54739</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8408756$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Jensen, William R.</creatorcontrib><creatorcontrib>Strangas, Elias G.</creatorcontrib><creatorcontrib>Foster, Shanelle N.</creatorcontrib><title>A Method for Online Stator Insulation Prognosis for Inverter-Driven Machines</title><title>IEEE transactions on industry applications</title><addtitle>TIA</addtitle><description>A significant portion of faults experienced by electrical machines is caused by degraded insulation. In order to reduce the effects of a failure, it is important to monitor the health of the insulation, preferably while the machine continues operation without any expensive equipment. In this paper, an online method to calculate the remaining useful lifetime (RUL) of the stator insulation with a simple equipment is proposed. The accelerated degradation testing was performed by exposing the stator of an electric machine to high temperatures. An extended Kalman filter algorithm is developed to calculate the RUL. A simple analog circuit is used to show how lower sampling rates can be used to capture the necessary information for prognosis. With this circuit, the same trend used to provide a prognosis for the insulation can be measured online without using any expensive or special technology.</description><subject>Accelerated tests</subject><subject>Analog circuits</subject><subject>Capacitance</subject><subject>Current measurement</subject><subject>Degradation</subject><subject>Electrical machines</subject><subject>Extended Kalman filter</subject><subject>extended Kalman filter (EKF)</subject><subject>fault prognosis</subject><subject>Insulation</subject><subject>leakage current</subject><subject>Leakage currents</subject><subject>Mathematical analysis</subject><subject>Prognosis</subject><subject>Prognostics and health management</subject><subject>Stators</subject><issn>0093-9994</issn><issn>1939-9367</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEFLAzEQRoMoWKt3wcuC562TZHeTOZZqdaGlgvUcYjZrt9SkJtuC_97UFk_DMO-bYR4htxRGlAI-LOvxiAGVIybLogB5RgYUOebIK3FOBgDIc0QsLslVjGsAWpS0GJDZOJvbfuWbrPUhW7hN52z21us-dbWLu43uO--y1-A_nY9d_MNqt7ehtyF_DN3eumyuzSrl4jW5aPUm2ptTHZL36dNy8pLPFs_1ZDzLDS9Fn1clZaWmwCttUKJpKVKOjWAFR9tKwUTVfkjTNKyRDTLN0oNGC6FNkxIAfEjuj3u3wX_vbOzV2u-CSydVYiWwCipMFBwpE3yMwbZqG7ovHX4UBXVwppIzdXCmTs5S5O4Y6ay1_7hMI1FW_BfqyWb5</recordid><startdate>201811</startdate><enddate>201811</enddate><creator>Jensen, William R.</creator><creator>Strangas, Elias G.</creator><creator>Foster, Shanelle N.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-4699-3493</orcidid><orcidid>https://orcid.org/0000-0001-9630-5500</orcidid></search><sort><creationdate>201811</creationdate><title>A Method for Online Stator Insulation Prognosis for Inverter-Driven Machines</title><author>Jensen, William R. ; Strangas, Elias G. ; Foster, Shanelle N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c357t-65125a1036ac989cf19139d72439ef87276fb8cdd2d8d92a2110ca77acd6ac003</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Accelerated tests</topic><topic>Analog circuits</topic><topic>Capacitance</topic><topic>Current measurement</topic><topic>Degradation</topic><topic>Electrical machines</topic><topic>Extended Kalman filter</topic><topic>extended Kalman filter (EKF)</topic><topic>fault prognosis</topic><topic>Insulation</topic><topic>leakage current</topic><topic>Leakage currents</topic><topic>Mathematical analysis</topic><topic>Prognosis</topic><topic>Prognostics and health management</topic><topic>Stators</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jensen, William R.</creatorcontrib><creatorcontrib>Strangas, Elias G.</creatorcontrib><creatorcontrib>Foster, Shanelle N.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on industry applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Jensen, William R.</au><au>Strangas, Elias G.</au><au>Foster, Shanelle N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Method for Online Stator Insulation Prognosis for Inverter-Driven Machines</atitle><jtitle>IEEE transactions on industry applications</jtitle><stitle>TIA</stitle><date>2018-11</date><risdate>2018</risdate><volume>54</volume><issue>6</issue><spage>5897</spage><epage>5906</epage><pages>5897-5906</pages><issn>0093-9994</issn><eissn>1939-9367</eissn><coden>ITIACR</coden><abstract>A significant portion of faults experienced by electrical machines is caused by degraded insulation. In order to reduce the effects of a failure, it is important to monitor the health of the insulation, preferably while the machine continues operation without any expensive equipment. In this paper, an online method to calculate the remaining useful lifetime (RUL) of the stator insulation with a simple equipment is proposed. The accelerated degradation testing was performed by exposing the stator of an electric machine to high temperatures. An extended Kalman filter algorithm is developed to calculate the RUL. A simple analog circuit is used to show how lower sampling rates can be used to capture the necessary information for prognosis. With this circuit, the same trend used to provide a prognosis for the insulation can be measured online without using any expensive or special technology.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIA.2018.2854408</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-4699-3493</orcidid><orcidid>https://orcid.org/0000-0001-9630-5500</orcidid></addata></record> |
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| source | IEEE Electronic Library (IEL) |
| subjects | Accelerated tests Analog circuits Capacitance Current measurement Degradation Electrical machines Extended Kalman filter extended Kalman filter (EKF) fault prognosis Insulation leakage current Leakage currents Mathematical analysis Prognosis Prognostics and health management Stators |
| title | A Method for Online Stator Insulation Prognosis for Inverter-Driven Machines |
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