Abstract
It is of important to recognize the mechanical fault for extra-high voltage Circuit Breakers (CBs) in GIS, when the condition monitoring of CBs is realized. In this paper, a new efficiency fault recognition method is provided, by using improved Support Vector Machines (LibSVMs). The recognition methods, ANN and LibSVM are compared on their recognition accuracy, and the results show that the LibSVM is more efficient than ANN. The algorithm of LibSVM is improved by using Genetic Algorithm (GA), and the GA-LibSVM can obtain higher recognition accuracy than usual LibSVM for mechanical fault recognition of CB.
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