污水处理系统智能软测量方法研究

Zaiwen Liu, Zhengxiang Wang, Fuxia Xue, C. Hou, Guoqiang Qi
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引用次数: 0

摘要

提出了基于径向基函数(RBF)神经网络的SBR污水处理出水水质智能软测量方法,以及RBF神经网络的结构和仿真。采用软测量和模糊控制方法可以解决SBR过程数学模型建立困难和SBR系统实时控制困难的问题。这为污水处理过程的实时控制创造了必要条件。结果表明,模拟的RBF神经网络可用于SBR出水BOD的软测量,该模型可用于预测实际水质样品输出,仿真结果表明,利用RBF神经网络建立软测量模型是可行的,模型是正确合理的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on the intelligent soft sensing method for sewage disposal system
Intelligent soft sensing method based on the radial basic function (RBF) neural network for water quality of outlet in SBR sewage disposal process, and the structure and simulation of RBF neural network are proposed in this paper. The problems that are difficult to establish mathematic model of SBR process and to apply real- time control in SBR system can be solved through adopting the soft sensing and fuzzy control method. This creates an essential condition for the real time control in sewage disposal process. The result shows that the simulated RBF neural network may be used to fulfill soft sensing for effluent BOD from SBR, and the model can be used to predict the practical water quality sample output The simulation result indicates that it is feasible for using RBF neural network to establish soft-sensing model and the model is correct and rational.
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