Journal
MECHANICAL AND MATERIALS ENGINEERING
Volume 554, Issue -, Pages 608-612Publisher
TRANS TECH PUBLICATIONS LTD
DOI: 10.4028/www.scientific.net/AMM.554.608
Keywords
Surge arrester; Thermography Analysis; Neural Network; Condition Monitoring; Age diagnostics
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Surge arresters, as protective equipment, are used to limit any overvoltage in a power system resulting from various sources. The surge arrester affects from degradation due to the continuous operating voltage system as well as due to repeated lightning current discharge. Therefore, condition monitoring and health diagnostics of surge arresters are a necessary issue. Hence, as a feasible solution, a condition monitoring based on leakage current measurement techniques was selected to tackle the problem of age diagnostics of surge arresters. The Particle Swarm Search Algorithm was introduced as a method for extracting the third harmonic resistive component, Ir3rd, from the total leakage current. To employ this method for extracting Ir3rd, codes were developed in Matlab. The setting of Particle Swarm Search Algorithm was configured for extracting Ir3rd and accuracy of 94% was obtained.
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