在污水处理过程中,出水总磷(Total Phosphorus,TP)是衡量污水处理效果的关键参数之一。本文针对目前出水TP难以实时测量的问题,提出了一种基于模糊神经网络(FNN)的出水TP软测量方法。该软测量方法通过实际运行数据,利用偏最小二乘法(Partial Least Squares,PLS)筛选出与出水TP相关性强的过程变量;同时,利用FNN建立了出水TP与相关性变量之间的软测量模型,并将该方法嵌入到污水处理运行系统。实验结果显示该软测量方法能够实现出水TP的实时预测,并且具有较好的预测精度。
【英文摘要】
Total Phosphorus(TP) is a key parameter to evaluate the performance of a wastewater treatment plant(WWTP). A soft-sensor monitoring method modelling by fuzzy neural network(FNN) was proposed in this paper to solve the problem of time-delay in TP measurement. To ensure accuracy and computing efficiency of soft-sensor model, the data used in this paper was obtained from a WWTP in China and Partial Least Squares(PLS) technique was utilized to suppress the irrelevant process variables with effluent TP. The soft...
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