A Genetic-Algorithm-Optimized Fractal Model to Predict the Constriction Resistance From Surface Roughness Measurements
The electrical contact resistance greatly influences the thermal behavior of substation connectors and other electrical equipment. During the design stage of such electrical devices, it is essential to accurately predict the contact resistance to achieve an optimal thermal behavior, thus ensuring co...
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| Veröffentlicht in: | IEEE transactions on instrumentation and measurement 2017-09, Vol.66 (9), p.2437-2447 |
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| container_title | IEEE transactions on instrumentation and measurement |
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| creator | Capelli, Francesca Riba, Jordi-Roger Ruperez, Elisa Sanllehi, Josep |
| description | The electrical contact resistance greatly influences the thermal behavior of substation connectors and other electrical equipment. During the design stage of such electrical devices, it is essential to accurately predict the contact resistance to achieve an optimal thermal behavior, thus ensuring contact stability and extended service life. This paper develops a genetic algorithm (GA) approach to determine the optimal values of the parameters of a fractal model of rough surfaces to accurately predict the measured value of the surface roughness. This GA-optimized fractal model provides an accurate prediction of the contact resistance when the electrical and mechanical properties of the contacting materials, surface roughness, contact pressure, and apparent area of contact are known. Experimental results corroborate the usefulness and accuracy of the proposed approach. Although the proposed model has been validated for substation connectors, it can also be applied in the design stage of many other electrical equipments. |
| doi_str_mv | 10.1109/TIM.2017.2707938 |
| format | Article |
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During the design stage of such electrical devices, it is essential to accurately predict the contact resistance to achieve an optimal thermal behavior, thus ensuring contact stability and extended service life. This paper develops a genetic algorithm (GA) approach to determine the optimal values of the parameters of a fractal model of rough surfaces to accurately predict the measured value of the surface roughness. This GA-optimized fractal model provides an accurate prediction of the contact resistance when the electrical and mechanical properties of the contacting materials, surface roughness, contact pressure, and apparent area of contact are known. Experimental results corroborate the usefulness and accuracy of the proposed approach. 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(IEEE) 2017</rights><rights>info:eu-repo/semantics/openAccess</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-964ac690f83b5ad3cf0e7daf69a5fcd2afd8a8157a9427d7218b3f5ccec529343</citedby><cites>FETCH-LOGICAL-c375t-964ac690f83b5ad3cf0e7daf69a5fcd2afd8a8157a9427d7218b3f5ccec529343</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7945532$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,314,776,780,792,881,26951,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7945532$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Capelli, Francesca</creatorcontrib><creatorcontrib>Riba, Jordi-Roger</creatorcontrib><creatorcontrib>Ruperez, Elisa</creatorcontrib><creatorcontrib>Sanllehi, Josep</creatorcontrib><title>A Genetic-Algorithm-Optimized Fractal Model to Predict the Constriction Resistance From Surface Roughness Measurements</title><title>IEEE transactions on instrumentation and measurement</title><addtitle>TIM</addtitle><description>The electrical contact resistance greatly influences the thermal behavior of substation connectors and other electrical equipment. During the design stage of such electrical devices, it is essential to accurately predict the contact resistance to achieve an optimal thermal behavior, thus ensuring contact stability and extended service life. This paper develops a genetic algorithm (GA) approach to determine the optimal values of the parameters of a fractal model of rough surfaces to accurately predict the measured value of the surface roughness. This GA-optimized fractal model provides an accurate prediction of the contact resistance when the electrical and mechanical properties of the contacting materials, surface roughness, contact pressure, and apparent area of contact are known. Experimental results corroborate the usefulness and accuracy of the proposed approach. Although the proposed model has been validated for substation connectors, it can also be applied in the design stage of many other electrical equipments.</description><subject>Algorismes genètics</subject><subject>Connectors</subject><subject>Connectors elèctrics</subject><subject>Contact pressure</subject><subject>Contact resistance</subject><subject>Control elèctric</subject><subject>Electric connectors</subject><subject>Electric contacts</subject><subject>Electric equipment</subject><subject>Electrical resistance</subject><subject>Enginyeria elèctrica</subject><subject>Fractal models</subject><subject>Fractals</subject><subject>Genetic algorithms</subject><subject>genetic algorithms (GAs)</subject><subject>Lògica matemàtica</subject><subject>Maquinària i aparells elèctrics</subject><subject>Matemàtiques i estadística</subject><subject>Materials</subject><subject>Mechanical properties</subject><subject>Resistència de materials</subject><subject>Rough surfaces</subject><subject>Service life</subject><subject>Substations</subject><subject>Surface resistance</subject><subject>Surface roughness</subject><subject>Testing</subject><subject>Thermal resistance</subject><subject>Thermodynamic properties</subject><subject>Àrees temàtiques de la UPC</subject><issn>0018-9456</issn><issn>1557-9662</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>XX2</sourceid><recordid>eNpFkUtLAzEURoMoWB97wU3A9dQ8JpPJshRfYFF8rEPM3NhIZ1KTjKC_3pQWXVwuH3zncuEgdEbJlFKiLl_uFlNGqJwySaTi7R6aUCFkpZqG7aMJIbStVC2aQ3SU0gchRDa1nKCvGb6BAbK31Wz1HqLPy756WGff-x_o8HU0NpsVXoQOVjgH_Bih8zbjvAQ8D0PKsSQfBvwEyadsBgsFCj1-HqMzJTyF8X05QEp4ASaNEXoYcjpBB86sEpzu9jF6vb56md9W9w83d_PZfWW5FLk8XxvbKOJa_iZMx60jIDvjGmWEsx0zrmtNS4U0qmayk4y2b9wJa8EKpnjNjxHd3rVptDqChWhN1sH4_7AZRiTTTDFGZWEutsw6hs8RUtYfYYxDeVOzUuA1aaUoLbK7HENKEZxeR9-b-K0p0RsjuhjRGyN6Z6Qg51vEA8BfXRYrgjP-C2fUiPw</recordid><startdate>20170901</startdate><enddate>20170901</enddate><creator>Capelli, Francesca</creator><creator>Riba, Jordi-Roger</creator><creator>Ruperez, Elisa</creator><creator>Sanllehi, Josep</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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During the design stage of such electrical devices, it is essential to accurately predict the contact resistance to achieve an optimal thermal behavior, thus ensuring contact stability and extended service life. This paper develops a genetic algorithm (GA) approach to determine the optimal values of the parameters of a fractal model of rough surfaces to accurately predict the measured value of the surface roughness. This GA-optimized fractal model provides an accurate prediction of the contact resistance when the electrical and mechanical properties of the contacting materials, surface roughness, contact pressure, and apparent area of contact are known. Experimental results corroborate the usefulness and accuracy of the proposed approach. Although the proposed model has been validated for substation connectors, it can also be applied in the design stage of many other electrical equipments.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIM.2017.2707938</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Algorismes genètics Connectors Connectors elèctrics Contact pressure Contact resistance Control elèctric Electric connectors Electric contacts Electric equipment Electrical resistance Enginyeria elèctrica Fractal models Fractals Genetic algorithms genetic algorithms (GAs) Lògica matemàtica Maquinària i aparells elèctrics Matemàtiques i estadística Materials Mechanical properties Resistència de materials Rough surfaces Service life Substations Surface resistance Surface roughness Testing Thermal resistance Thermodynamic properties Àrees temàtiques de la UPC |
| title | A Genetic-Algorithm-Optimized Fractal Model to Predict the Constriction Resistance From Surface Roughness Measurements |
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