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Naïve Bayes classifier for temporary short circuit fault detection in stator winding
This paper is proposing Naïve Bayes classifier detection system to identify the symptom of stator winding deterioration. The proposed system is based on probabilistic classifier with strong independence assumption of each fault case. The temporary short circuit case is defined as non permanent shor...
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creator | Asfani, D. A. Purnomo, M. H. Sawitri, D. R. |
description | This paper is proposing Naïve Bayes classifier detection system to identify the symptom of stator winding deterioration. The proposed system is based on probabilistic classifier with strong independence assumption of each fault case. The temporary short circuit case is defined as non permanent short circuit fault with high impedance. This fault case is representing the early stage of stator insulation break down. The laboratory experiment is performed to simulate the fault cases consist of induction motor with stator modification and current measurement system. The detection system is trained to identify the temporary short circuit occurrence consist of transient starting, steady state and ending of temporary short circuit. The system is also tested using non trained data to clarify the detection performance. |
doi_str_mv | 10.1109/DEMPED.2013.6645730 |
format | conference_proceeding |
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A. ; Purnomo, M. H. ; Sawitri, D. R.</creator><creatorcontrib>Asfani, D. A. ; Purnomo, M. H. ; Sawitri, D. R.</creatorcontrib><description>This paper is proposing Naïve Bayes classifier detection system to identify the symptom of stator winding deterioration. The proposed system is based on probabilistic classifier with strong independence assumption of each fault case. The temporary short circuit case is defined as non permanent short circuit fault with high impedance. This fault case is representing the early stage of stator insulation break down. The laboratory experiment is performed to simulate the fault cases consist of induction motor with stator modification and current measurement system. The detection system is trained to identify the temporary short circuit occurrence consist of transient starting, steady state and ending of temporary short circuit. The system is also tested using non trained data to clarify the detection performance.</description><identifier>EISBN: 1479900257</identifier><identifier>EISBN: 9781479900251</identifier><identifier>DOI: 10.1109/DEMPED.2013.6645730</identifier><language>eng</language><publisher>IEEE</publisher><subject>bayesian methods ; Circuit faults ; Estimation ; Fault detection ; induction motor ; Induction motors ; Kernel ; Stator windings ; stators ; Wavelet transforms</subject><ispartof>2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED), 2013, p.288-294</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/6645730$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6645730$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Asfani, D. A.</creatorcontrib><creatorcontrib>Purnomo, M. H.</creatorcontrib><creatorcontrib>Sawitri, D. R.</creatorcontrib><title>Naïve Bayes classifier for temporary short circuit fault detection in stator winding</title><title>2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)</title><addtitle>DEMPED</addtitle><description>This paper is proposing Naïve Bayes classifier detection system to identify the symptom of stator winding deterioration. The proposed system is based on probabilistic classifier with strong independence assumption of each fault case. The temporary short circuit case is defined as non permanent short circuit fault with high impedance. This fault case is representing the early stage of stator insulation break down. The laboratory experiment is performed to simulate the fault cases consist of induction motor with stator modification and current measurement system. The detection system is trained to identify the temporary short circuit occurrence consist of transient starting, steady state and ending of temporary short circuit. The system is also tested using non trained data to clarify the detection performance.</description><subject>bayesian methods</subject><subject>Circuit faults</subject><subject>Estimation</subject><subject>Fault detection</subject><subject>induction motor</subject><subject>Induction motors</subject><subject>Kernel</subject><subject>Stator windings</subject><subject>stators</subject><subject>Wavelet transforms</subject><isbn>1479900257</isbn><isbn>9781479900251</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj0tOwzAURc0ACShdQSfeQMJzHMf1ENpCkcpnQMfVi_0MRmlS2S6oq2IRbIxKdHRH5-hcxiYCSiHA3MwXT6-LeVmBkGXT1EpLOGNXotbGAFRKX7BxSp8AILQWAPKSrZ_x9-eL-B0eKHHbYUrBB4rcD5Fn2u6GiPHA08cQM7ch2n3I3OO-y9xRJpvD0PPQ85QxH4nv0LvQv1-zc49dovFpR2x9v3ibLYvVy8Pj7HZVBKFVLqbUkK9Eg9XUaQJnFUlLYAnROylqUAocGdM2gK3UCnxbgTGaZG2tMbUcscm_NxDRZhfD9hi7OT2Xf9fkUbI</recordid><startdate>201308</startdate><enddate>201308</enddate><creator>Asfani, D. A.</creator><creator>Purnomo, M. H.</creator><creator>Sawitri, D. R.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201308</creationdate><title>Naïve Bayes classifier for temporary short circuit fault detection in stator winding</title><author>Asfani, D. A. ; Purnomo, M. H. ; Sawitri, D. R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-8e6ef216a28d7e0dc5e3ce0ceaafd3140550de99b60ab3750fb20997e34cc9943</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>bayesian methods</topic><topic>Circuit faults</topic><topic>Estimation</topic><topic>Fault detection</topic><topic>induction motor</topic><topic>Induction motors</topic><topic>Kernel</topic><topic>Stator windings</topic><topic>stators</topic><topic>Wavelet transforms</topic><toplevel>online_resources</toplevel><creatorcontrib>Asfani, D. A.</creatorcontrib><creatorcontrib>Purnomo, M. H.</creatorcontrib><creatorcontrib>Sawitri, D. R.</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/IET 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>Asfani, D. A.</au><au>Purnomo, M. H.</au><au>Sawitri, D. R.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Naïve Bayes classifier for temporary short circuit fault detection in stator winding</atitle><btitle>2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)</btitle><stitle>DEMPED</stitle><date>2013-08</date><risdate>2013</risdate><spage>288</spage><epage>294</epage><pages>288-294</pages><eisbn>1479900257</eisbn><eisbn>9781479900251</eisbn><abstract>This paper is proposing Naïve Bayes classifier detection system to identify the symptom of stator winding deterioration. The proposed system is based on probabilistic classifier with strong independence assumption of each fault case. The temporary short circuit case is defined as non permanent short circuit fault with high impedance. This fault case is representing the early stage of stator insulation break down. The laboratory experiment is performed to simulate the fault cases consist of induction motor with stator modification and current measurement system. The detection system is trained to identify the temporary short circuit occurrence consist of transient starting, steady state and ending of temporary short circuit. The system is also tested using non trained data to clarify the detection performance.</abstract><pub>IEEE</pub><doi>10.1109/DEMPED.2013.6645730</doi><tpages>7</tpages></addata></record> |
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language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | bayesian methods Circuit faults Estimation Fault detection induction motor Induction motors Kernel Stator windings stators Wavelet transforms |
title | Naïve Bayes classifier for temporary short circuit fault detection in stator winding |
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