Inverse S-Transform Based Decision Tree for Power System Faults Identification

Abstract

 In this paper a decision tree based identification of power system faults has been proposed. The key input values to the decision tree are the performance indices calculated from the maximum values of unfiltered inverse Stockwell transform (MUNIST) technique. A wide range of techniques including Stockwell transform (ST) have been used for the identification of power system faults. However, the signatures produced by these techniques are not unique and sometimes lead to misinterpretation of faults. Consequently, a decision tree based on the inverse Stockwell transform method is proposed in the present paper to automatically identify both the symmetrical and unsymmetrical power system faults. The method is able to determine both sudden and gradual changes in the signal caused by different power system faults. The technique is very accurate and produces unique signatures compared to the existing techniques. The results obtained show the efficacy of the proposed technique.