污水厂曝气系统的优化控制研究

发布时间：2018-01-17 19:21

本文关键词：污水厂曝气系统的优化控制研究　出处：《昆明理工大学》2017年硕士论文　论文类型：学位论文

更多相关文章： 溶解氧 软测量 模糊PID 神经网络

【摘要】：我国是一个工业相对发达的国家,工业发展的迅速,必然会导致环境污染的加剧,其中水污染逐渐成为人们比较关注的话题。自然而然污水处理受到了高度的重视。我国污水处理的自动化水平相对而言较低,大多数还处在人工现场操作阶段,或者是通过工控软件远程点动的操作的方式上。自动化程度高一些的污水厂,无非也是采取一些简单的PI控制,或者传统的PID控制方式,这样虽然效率有所提高,但还是取得不了很好的控制效果。同样造成大量的浪费,整个污水厂的运行成本没有显著的下降。在整个污水处理系统中,曝气系统是其中一个非常重要的环节,它的能耗占整个污水处理系统的一半以上,并且对出水的水质起到了关键的作用。所以,曝气系统模型的精确建立并加以先进的控制算法,可以很好的提高整个污水系统的运行效率,降低运行成本。本文针对北京某污水厂的智能曝气控制系统改造项目,并结合污水厂的工艺流程及控制方式进行分析。选用溶解氧DO做为系统的的被控参数。但污水处理过程相当复杂,具有参数时变,非线性,滞后性等特点。所以很难精确的建立溶解氧DO的机理模型。因此我们选用溶解氧DO为主导变量,并选用一些其它与其相关性高且易于获取的数据作为辅助变量,再结合神经网络来建立溶解氧的软测量模型,得到精度较高的软测量模型。针对传统PID控制方式很难取得满意效果的问题,对其加以模糊控制算法,并在MATLAB平台下进行了仿真,取得相对较好的控制效果。最终我们结合实际工程改造。将模糊控制规则加在西门子300PLC程序当中,并结合PLC当中自带的PID块,对溶解氧进行控制,通过改造前后溶解氧曲线的对比得出了,明显看出改造之后的效果明显优于之前的控制方式。而且观察优化前后的鼓风机房耗电量的多少,可以看到确实取得了节能的效果。
[Abstract]:China is a country with relatively developed industry. The rapid development of industry will inevitably lead to the aggravation of environmental pollution. Water pollution has gradually become a topic of concern. Natural sewage treatment has been highly valued. The automation level of sewage treatment in China is relatively low, and most of them are still in the stage of artificial field operation. Or through the industrial control software remote point operation mode. Higher degree of automation of sewage plants, but also take some simple Pi control, or the traditional PID control mode. Although the efficiency has been improved, but still can not achieve a good control effect. Also caused a lot of waste, the entire sewage treatment plant operating costs have not significantly decreased. In the entire sewage treatment system. Aeration system is one of the most important links, its energy consumption accounts for more than half of the total sewage treatment system, and it plays a key role in the quality of effluent. The accurate establishment of aeration system model and advanced control algorithm can improve the operation efficiency of the whole sewage system. This paper aims at the renovation project of intelligent aeration control system in a sewage treatment plant in Beijing. The dissolved oxygen do is selected as the controlled parameter of the system, but the process of sewage treatment is quite complex, with time-varying parameters and nonlinear. Therefore, it is difficult to establish the mechanism model of do precisely. So we choose do as the leading variable. Some other data which are highly relevant and easy to obtain are selected as auxiliary variables, and then the soft-sensing model of dissolved oxygen is established by combining neural network. To solve the problem that the traditional PID control method is difficult to achieve satisfactory results, fuzzy control algorithm is applied to the model, and the simulation is carried out on the MATLAB platform. Finally, we combined with the actual engineering transformation. The fuzzy control rules are added to Siemens 300 PLC program, and combined with the PID block in PLC. Through the contrast of the dissolved oxygen curve before and after the transformation, it is obvious that the effect of the transformation is better than that of the previous control mode, and the power consumption of the blower room before and after optimization is observed. It can be seen that the effect of energy saving has been achieved.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：X703;TP273

【参考文献】