基于神经网络的生化池污水毒性软测量

Soft Measurement for Wastewater Toxicity of Biochemical Pool Based on Neural Network

文中叙述了污水中有毒物质对活性污泥的有毒效应(即生化池污水毒性)及其对整个污水生化处理系统的影响。通过分析有毒污水对生化池相关参数的影响,提出了基于径向基函数(RBF)神经网络的软测量方法。并从工程应用角度将人工神经网络软测量方法应用于生化池污水毒性指标的实时检测。在永和污水厂的试用中证明了这种方法的有效性。

This paper describes the influence of toxic substances in the wastewater produces to the activity of activated sludge and the wastewater treatment systems. After analyzing the impacts of toxic wastewater to the operating parameters in the biochemical pool, present a soft-sensing method for the measurement, which is based on the radial basis functional （RBF） neural networks. But also use this algorithm in the real-time measurement of the toxicity of the wastewater of the biochemical pool. The effectiveness of this method is approved in Yonghe sewage farm.