Application of fuzzy ARTmap for fault monitoring on complex transmission systems

The work described in this paper addresses the problem of fault monitoring on complex transmission systems, in particular due to mutual coupling between the two circuits under different fault conditions; the problem is compounded by the fact that this mutual coupling is highly non-linear. In this respect, artificial intelligence (AI) techniques provide the ability to classify the faulted phase/phases by identifying different patterns of the associated voltages and currents. In this paper, a fuzzy ARTmap is employed and is found to be particularly suitable for solving the complex fault classification problem under various system and fault conditions. Particular emphasis is placed on introducing the background of AI techniques as applied to the specific problem and then describing the methodology adopted for training the fuzzy ARTmap neural network, which is proving to be a very useful tool for power system engineers. Furthermore, the classification technique based on the fuzzy ARTmap is compared with the error back-propagation (EBP) training algorithm, and it is shown that the former technique is better suited for solving the fault monitoring problem in complex transmission systems