Parametric and Nonparametric Models for Lifespan Modeling of Insulation Systems in Electrical Machines
This paper describes an original statistical approach for the lifespan modeling of electric machine insulation materials. The presented models aim to study the effect of three main stress factors (voltage, frequency, and temperature) and their interactions on the insulation lifespan. The proposed me...
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| Veröffentlicht in: | IEEE transactions on industry applications 2017-05, Vol.53 (3), p.3119-3128 |
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| creator | Salameh, Farah Picot, Antoine Chabert, Marie Maussion, Pascal |
| description | This paper describes an original statistical approach for the lifespan modeling of electric machine insulation materials. The presented models aim to study the effect of three main stress factors (voltage, frequency, and temperature) and their interactions on the insulation lifespan. The proposed methodology is applied to two different insulation materials tested in partial discharge regime. Accelerated ageing tests are organized according to experimental optimization methods in order to minimize the experimental cost while ensuring the best model accuracy. In addition to classical parametric models, the life-stress relationship is expressed through original nonparametric and hybrid models that have never been investigated in insulation aging studies before. These two models present the original contribution of this paper. For each material, models are computed from organized sets of experiments and applied on a randomly configured test set for validity checking. The different models are evaluated and compared in order to define their optimal use. |
| doi_str_mv | 10.1109/TIA.2016.2635100 |
| format | Article |
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The presented models aim to study the effect of three main stress factors (voltage, frequency, and temperature) and their interactions on the insulation lifespan. The proposed methodology is applied to two different insulation materials tested in partial discharge regime. Accelerated ageing tests are organized according to experimental optimization methods in order to minimize the experimental cost while ensuring the best model accuracy. In addition to classical parametric models, the life-stress relationship is expressed through original nonparametric and hybrid models that have never been investigated in insulation aging studies before. These two models present the original contribution of this paper. For each material, models are computed from organized sets of experiments and applied on a randomly configured test set for validity checking. The different models are evaluated and compared in order to define their optimal use.</description><identifier>ISSN: 0093-9994</identifier><identifier>EISSN: 1939-9367</identifier><identifier>DOI: 10.1109/TIA.2016.2635100</identifier><identifier>CODEN: ITIACR</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Accelerated aging ; Accelerated tests ; Aging ; Biological system modeling ; Computational modeling ; design optimization ; electric machines ; Insulation ; Life span ; lifetime estimation ; model checking ; modeling ; Modelling ; Nonparametric statistics ; partial discharges (PD) ; regression analysis ; Service life assessment ; Stress ; Wires ; Wounds</subject><ispartof>IEEE transactions on industry applications, 2017-05, Vol.53 (3), p.3119-3128</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c333t-c12b33d91014ab2e7a6fdc3e1db7b29d8bde574137aec45d866aec4c3cb41c903</citedby><cites>FETCH-LOGICAL-c333t-c12b33d91014ab2e7a6fdc3e1db7b29d8bde574137aec45d866aec4c3cb41c903</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7862239$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54736</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7862239$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Salameh, Farah</creatorcontrib><creatorcontrib>Picot, Antoine</creatorcontrib><creatorcontrib>Chabert, Marie</creatorcontrib><creatorcontrib>Maussion, Pascal</creatorcontrib><title>Parametric and Nonparametric Models for Lifespan Modeling of Insulation Systems in Electrical Machines</title><title>IEEE transactions on industry applications</title><addtitle>TIA</addtitle><description>This paper describes an original statistical approach for the lifespan modeling of electric machine insulation materials. The presented models aim to study the effect of three main stress factors (voltage, frequency, and temperature) and their interactions on the insulation lifespan. The proposed methodology is applied to two different insulation materials tested in partial discharge regime. Accelerated ageing tests are organized according to experimental optimization methods in order to minimize the experimental cost while ensuring the best model accuracy. In addition to classical parametric models, the life-stress relationship is expressed through original nonparametric and hybrid models that have never been investigated in insulation aging studies before. These two models present the original contribution of this paper. For each material, models are computed from organized sets of experiments and applied on a randomly configured test set for validity checking. The different models are evaluated and compared in order to define their optimal use.</description><subject>Accelerated aging</subject><subject>Accelerated tests</subject><subject>Aging</subject><subject>Biological system modeling</subject><subject>Computational modeling</subject><subject>design optimization</subject><subject>electric machines</subject><subject>Insulation</subject><subject>Life span</subject><subject>lifetime estimation</subject><subject>model checking</subject><subject>modeling</subject><subject>Modelling</subject><subject>Nonparametric statistics</subject><subject>partial discharges (PD)</subject><subject>regression analysis</subject><subject>Service life assessment</subject><subject>Stress</subject><subject>Wires</subject><subject>Wounds</subject><issn>0093-9994</issn><issn>1939-9367</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpFkM1LAzEQxYMoWD_ugpeA56352M02x1KqFloVrOeQTWY1ZZusyfbQ_95dtuhphsd7M48fQneUTCkl8nG7mk8ZoWLKBC8oIWdoQiWXmeSiPEcTQiTPpJT5JbpKaUcIzQuaT1D9rqPeQxedwdpb_Bp8-69sgoUm4TpEvHY1pFb7UXP-C4car3w6NLpzweOPY-pgn7DzeNmAGeK6wRttvp2HdIMuat0kuD3Na_T5tNwuXrL12_NqMV9nhnPeZYayinMraV9PVwxKLWprOFBblRWTdlZZKMqc8lKDyQs7E2JYDDdVTo0k_Bo9jHfbGH4OkDq1C4fo-5eKSsKYKCgfXGR0mRhSilCrNrq9jkdFiRpoqp6mGmiqE80-cj9GHAD82cuZYIxL_gvsZHHN</recordid><startdate>201705</startdate><enddate>201705</enddate><creator>Salameh, Farah</creator><creator>Picot, Antoine</creator><creator>Chabert, Marie</creator><creator>Maussion, Pascal</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></search><sort><creationdate>201705</creationdate><title>Parametric and Nonparametric Models for Lifespan Modeling of Insulation Systems in Electrical Machines</title><author>Salameh, Farah ; Picot, Antoine ; Chabert, Marie ; Maussion, Pascal</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c333t-c12b33d91014ab2e7a6fdc3e1db7b29d8bde574137aec45d866aec4c3cb41c903</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Accelerated aging</topic><topic>Accelerated tests</topic><topic>Aging</topic><topic>Biological system modeling</topic><topic>Computational modeling</topic><topic>design optimization</topic><topic>electric machines</topic><topic>Insulation</topic><topic>Life span</topic><topic>lifetime estimation</topic><topic>model checking</topic><topic>modeling</topic><topic>Modelling</topic><topic>Nonparametric statistics</topic><topic>partial discharges (PD)</topic><topic>regression analysis</topic><topic>Service life assessment</topic><topic>Stress</topic><topic>Wires</topic><topic>Wounds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Salameh, Farah</creatorcontrib><creatorcontrib>Picot, Antoine</creatorcontrib><creatorcontrib>Chabert, Marie</creatorcontrib><creatorcontrib>Maussion, Pascal</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>Salameh, Farah</au><au>Picot, Antoine</au><au>Chabert, Marie</au><au>Maussion, Pascal</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Parametric and Nonparametric Models for Lifespan Modeling of Insulation Systems in Electrical Machines</atitle><jtitle>IEEE transactions on industry applications</jtitle><stitle>TIA</stitle><date>2017-05</date><risdate>2017</risdate><volume>53</volume><issue>3</issue><spage>3119</spage><epage>3128</epage><pages>3119-3128</pages><issn>0093-9994</issn><eissn>1939-9367</eissn><coden>ITIACR</coden><abstract>This paper describes an original statistical approach for the lifespan modeling of electric machine insulation materials. The presented models aim to study the effect of three main stress factors (voltage, frequency, and temperature) and their interactions on the insulation lifespan. The proposed methodology is applied to two different insulation materials tested in partial discharge regime. Accelerated ageing tests are organized according to experimental optimization methods in order to minimize the experimental cost while ensuring the best model accuracy. In addition to classical parametric models, the life-stress relationship is expressed through original nonparametric and hybrid models that have never been investigated in insulation aging studies before. These two models present the original contribution of this paper. For each material, models are computed from organized sets of experiments and applied on a randomly configured test set for validity checking. The different models are evaluated and compared in order to define their optimal use.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIA.2016.2635100</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Accelerated aging Accelerated tests Aging Biological system modeling Computational modeling design optimization electric machines Insulation Life span lifetime estimation model checking modeling Modelling Nonparametric statistics partial discharges (PD) regression analysis Service life assessment Stress Wires Wounds |
| title | Parametric and Nonparametric Models for Lifespan Modeling of Insulation Systems in Electrical Machines |
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