计算机技术与发展2011，Vol.21Issue(3)：243-245,3.
基于主元分析和神经网络的污水处理能耗分析
Analysis of Sewage Treatment Aeration Energy Consumption Based On PCA and BP Networks
摘要
Abstract
Sewage treatment plant is a high energy consumption industry by now, Sewage aeration energy consumption is the main of total sewage treatment plant energy consumption, nearly accounting for 60％ of the total. Present a simple, powerfid aeration energy consumption monitor model, which supplies the real time energy consumption through the influent quality parameters and other parameters.The model is helpful for advanced control system to adjust its control opinion. To make the model simple, PCA is used to choose the influent parameters affecting energy consumption strongly as few as possible. The model established by back-propagation network is trained and tested by sets of a sewage treatment plant operational data. The test result shows that the model works well with high efficiency and accuracy. The test result also shows aeration energy consumption is not only affected by influent flow,pH, biological oxygen demand ( BOD), but also affected by temperature in aeration tank in the sewage treatment plant.关键词
污水处理厂/曝气能耗/化学需氧景/生物需氧量/BP网络分类
信息技术与安全科学引用本文复制引用
王丽娟..基于主元分析和神经网络的污水处理能耗分析[J].计算机技术与发展,2011,21(3):243-245,3.基金项目
陕西省教育科研2009年度重点计划项目(09JK499) （09JK499）
