Application of near perfect reconstruction filter banks in power quality disturbances classification methods

The wavelet transform has been successfully used in the area of power quality analysis. There are many published papers with methods for power quality disturbances classification or harmonic measurement, which use wavelet transform. However, the properties of the wavelet transform can drastically vary from the choice of the wavelet. In this paper we analyze the influence of choice of the wavelet to the accuracy of the PQ classification methods. We test two classification methods with wavelets of frequently used families and support sizes. Also, we introduce near perfect reconstruction filter banks. The simulation results indicate that the Johnston's filters are a good choice, especially in the presence of noise.