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 (MUNISTKeywords: Decision tree, faults, identification, power system, signal processing IntroductionComplexity of the power system has become manifold due to an increase in the size and power levels of the present power system. Consequently, many studies like transient stability, power quality and instability etc. have taken a center stage in the power system analysis. The faulty operation of the power system components and absence of non ideal power system design leads to transients [1], [2]. These problems have large operational effect on the power system though the time interval of the transients is negligible. The transient stability analysis can be used for analyzing such events having time periods between seconds and few minutes. With the incorporation of a large number of sensitive and critical loads into the system as well as the inclusion of deregulation and competition in the power market, utilities are now more concerned in identifying, measuring and monitoring the transient events. Also, necessary corrective actions for their reduction and elimination have now become essential.Various types of relays have been developed to isolate the healthy circuit to be affected by the faults. However, action of the relay is same for all types of faults. This is possible if information about the type of fault is available to the system operator. However, to reduce the effect of transients exact precautionary actions are of massive importance. The information about the fault is still in need, and the utilities are also concerned about the reason behind the

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