Denoising of Generator Output Power based on the wavelet transform

Abstract

Real-time Generator Output Power is an important parameter in the thermal power which shows the operation status of the adjusting and control equipments. Wavelets are mathematical functions that cut up data into different frequency components, and then study each component with a resolution matched to its scale. In this paper, we used the wavelet transform to do the signal denoising of the Generator Output Power which makes the data curve more easily understood without rapid fluctuation. The wavelet used here was “db3”. The structure of multilevel 1-D wavelet in level-5 decomposition was used in the experiment. The results show that the data analysis using wavelet transform can decrease the rapid fluctuation of the data, which make the data mining more easily in the long-time. The method can be widely used in the long-time data storage, research and prediction.