Denoising of Inflow of Pingzhai Reservoir Based on Fusion Algorithm of Wavelet Transform and Savitzky-Golay Filter - GAO Lin; SONG Jinwei; LI Zuoxiao (Renmin Zhujiang)
In response to abnormal fluctuations of water flow in the shape of a "sawtooth" in the reverse inference of water balance, a wavelet transform Savitzky-Golay filter fusion algorithm was proposed. The algorithm first performed wavelet decomposition and threshold denoising preprocessing on the research data by setting different parameter combinations. Wavelet basis functions and decomposition levels were then selected. Based on this, the Savitzky-Golay filter was used to perform secondary denoising on the preprocessed data, to further eliminate residual low-level noise and improve the overall smoothing effect. Finally, the inverse wavelet transform was employed to reconstruct the complete signal process. The window length and polynomial order were further optimized through denoising evaluation indicators to achieve wavelet transform Savitzky-Golay filter fusion denoising. This method was applied to the historical flood events of Pingzhai Reservoir to infer the inflow, and the relative error of flood peak, peak time difference, and smoothness were set as evaluation indicators. According to the results, compared with the five point three order smoothing method, sliding average method, and wavelet threshold denoising method, the wavelet transform SG filtering fusion algorithm significantly improves the smoothness and denoising effect while ensuring the characteristics of the reverse flow peak information of the inflow. The research results are of great significance for the refined management and optimized operation of Pingzhai Reservoir and serve as a reference for similar projects.