Recursive regression and Wiener deconvolution for coagulation optimization in water treatment plant

Chuhong Fei, T. Wong, Eric Morris, Ting Liu
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引用次数: 1

Abstract

A coagulation optimization strategy was developed which utilizes the Wiener deconvolution filter to estimate steady-steady values, and then updates the optimization model using recursive kernel regression. The regression-based dose controller is capable of maintaining a target turbidity level with changing raw water conditions. Various pilot test experiments were performed to validate the effectiveness of the proposed strategy.
递归回归和维纳反卷积在水处理厂混凝优化中的应用
提出了一种混凝优化策略,利用维纳反卷积滤波器估计稳态值,然后利用递归核回归对优化模型进行更新。基于回归的剂量控制器能够在不断变化的原水条件下保持目标浊度水平。为了验证所提策略的有效性,进行了各种中试实验。
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