基于组态软件的DMF回收智能控制系统的应用研究

发布时间：2018-02-25 23:00

本文关键词： DMF回收 S7-300PLC 组态王智能控制神经网络　出处：《合肥工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：伴随着化工企业的快速发展,人们对DMF的认识越来越丰富。为防止其污染环境,也为降低生产成本、节约资源,更多的企业选择对DMF采取回收处理。基于回收系统的复杂性,企业在此耗费了大量的人力,且生产效率低下,影响经济效益。本文就是在此背景下,根据客户企业的要求,结合生产现场具体情况,提出控制系统的设计方案。本文所设计的DMF回收控制系统,是一种分布式控制系统。该控制系统的设计是采用了西门子S7-300系列的PLC作为主要控制器。采用PID控制模块FM355C作为硬件基础,实现如流量、液位、压力等模拟量的闭环控制。编程软件STEP7用于实现系统的硬件组态和控制程序的编写。控制系统的人机界面的设计方面,是把两个组态软件相互配合。组态王作为远程控制室中上位机的人机界面平台,实现对生产现场的实时监测和控制。WINCC软件作为生产现场控制端上位机的人机界面平台,只负责数据的显示和监测。为改善回收系统的自动化水平和提高生产效率,本文针对精馏处理过程中导热油阀门的控制问题进行研究。文中提出了神经网络分类器、模糊神经网络分类器,以及遗传神经网络分类器的设计方案。并且做出了仿真结果,从而验证它们的可行性和先进性。
[Abstract]:With the rapid development of chemical enterprises, more and more people know more and more about DMF. In order to prevent environmental pollution, reduce production cost and save resources, more enterprises choose to take the DMF recovery treatment based on the complexity of recycling system. The enterprise consumes a lot of manpower here, and the production efficiency is low, which affects the economic benefit. In this context, according to the requirements of the customer enterprises, combined with the specific situation of the production site, The design scheme of the control system is put forward. The DMF recovery control system designed in this paper, This control system is designed with Siemens S7-300 series PLC as the main controller, PID control module FM355C as the hardware base, such as flow rate, liquid level, etc. Closed loop control of analog variables such as pressure. The programming software STEP7 is used to realize the hardware configuration of the system and the programming of the control program, and the design of the man-machine interface of the control system, The two configuration software cooperate with each other. Kingview is the man-machine interface platform of the upper computer in the remote control room, and realizes the real-time monitoring and control of the production site. WinCC software is used as the man-machine interface platform of the upper computer in the control end of the production site. In order to improve the automation level of the recovery system and improve the production efficiency, this paper studies the control problem of the heat conduction oil valve in the rectification process. In this paper, a neural network classifier is proposed. The design scheme of fuzzy neural network classifier and genetic neural network classifier is given, and the simulation results are given to verify their feasibility and advanced nature.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP273

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