Disturbance identification based on mathematical morphology and radial coordinate visualization

This paper proposes a novel power quality disturbance identification algorithm based on mathematical morphology (MM) and radial coordinate visualization (Radviz). The algorithm firstly filters the noise out from the signals using mathematical median filter, and then extends the one-dimensional data to multi-dimensional data. Consequently, it is possible to use Radviz to decouple the normal part and the disturbance from each other, so that the disturbance can be identified more easily. Simulation studies have been conducted to test the performance of the proposed algorithm and the results have demonstrated its validity.