An Algorithm Based on Hilbert Transform and Rule Based Decision Tree Classification of Power Quality Disturbances

This research work presents an algorithm based on the Hilbert Transform and rule based decision tree for detection and classification of the single stage power quality disturbances. The power quality disturbances are generated in MATLAB software using mathematical relations. These signals are decomposed using Hilbert Transform. Features are extracted from output of the Hilbert Transform which is given as input to the rule based decision tree for classification purpose. The investigated single stage power quality disturbance include pure sine wave, voltage sag, voltage swell, momentary interruption (MI), oscillatory transient (OT), impulsive transient (IT), spike and notch. Effectiveness of the proposed approach is shown by calculating efficiency of the proposed algorithm on testing 50 data sets of each PQ disturbance obtained by varying the parameters of the disturbances.