An image processing based method for power quality event identification

This paper presents a novel technique to visualize and detect various power quality disturbance events. It is based on the image processing methods known as grayscale images and binary images. Gray image created from recorded disturbance voltage waveform is first represented as a transverse wave having compressions and rarefactions. Then using image enhancement techniques, the unique features of the disturbance waveform are visualized. Furthermore, the patterns obtained for a pure sine signal and the signal with disturbances are compared for identification of the signal with disturbance. The decision regarding the disturbance type is made using binary image analysis techniques. Finally, to exhibit the novelty of the proposed method, a comparison is made with a conventional image processing based power quality event detection method. In addition, evaluation studies for verifying the accuracy of the method are presented.

► Introduces a new image processing method for power quality event detection. ► Grayscale images and binary images are used to extract the features. ► The proposed method is compared with conventional image based method for validation. ► Results show the method is effective and suitable for visualization and detection of events.