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精炼炉底吹氩过程神经网络PID控制与优化研究

Research of Refining Furnance Bottom Blowing Argon Neural Networks PID Control and Optimize

【作者】 史纪波

【导师】 吴学礼;

【作者基本信息】 河北科技大学 , 计算机应用技术, 2011, 硕士

【摘要】 底吹氩技术是精炼炉进行二次精炼的一项重要技术,对提高钢材的质量具有重要的意义。目前国内的底吹氩基本都是手动操作,工人凭借工作经验来控制流量,这样就增加了失误率并且降低了工作效率。这种落后的监控和管理机制远不能适应生产和科技发展的要求。随着智能控制的迅速发展,实时控制与工艺优化成为当今底吹氩技术发展的趋势。本文首先介绍了论文的选题背景、底吹氩技术的国内外发展现状,对精炼炉底吹氩过程的工艺、原理、以及功能进行了概述。在此基础上对底吹氩供气系统进行分析,建立了底吹氩供气系统的数学模型。对精炼炉底吹氩供气系统的控制方法进行了研究。考虑到现场许多的干扰因素,底吹氩供气系统模型不易精确确定,对精炼炉底吹氩系统的BP神经网络PID控制方法进行了研究。本文利用MATLAB软件对所建立的模型进行了仿真研究和分析,将BP神经网络PID控制方法应用于底吹氩供气系统。在VC++6.0的环境下,利用C++语言设计了一套精炼炉底吹氩供气系统,以保证氩气流量能够按照设定值平稳的吹入钢包。首先介绍了系统的硬件选型以及模拟钢包的设计。本系统具有良好的人机界面,主要包括流量的设定、实时数据的动态曲线显示、实时数据的保存等功能。利用物理模拟的方法,在所建立的底吹氩供气系统上进行了底吹氩水模实验。在不同的吹氩量、不同的透气砖数目及其不同的布置方式下,针对搅拌效果开展了工艺优化研究,确定出搅拌效果较好和匀混时间较短的工艺参数,用于指导实际生产。

【Abstract】 The bottom blowing argon technology is an important technology in refining furnace for the secondary refining. It has great significance to enhance the quality of steel. At present, the workers operate bottom blowing argon in our country, and manipulate the flow of argon gas through their experience. This increases ratio of lapsus and decreases work efficiency. The laggard monitor and control and management mechanism can’t suit to the request of the yield and development of science and technology. Today, precision, convenience, and Real-time control become the developing trend of bottom blowing argon control, along with the progress of intelligent control.First, it has introduced the background of the topic, the development and current situation of bottom blowing argon technology home and abroad. There is an overview on handicraft, principle and function of furnace bottom blowing argon process. On this basis, there is a analysis about bottom blowing argon gas supply system and establishment its mathematics model. Then researched the control methods of the system. It is not easy for identify the modle accurately of the system because of there are more disruptive factors at the scene. So the BP neural network PID control method of bottom blowing argon gas supply system was researched. The article conduct research and analysis of simulation for the established model make use of the software named MATLAB and apply BP neural network PID control method to bottom blowing argon gas supply system.It designed a set of refining furnace bottom blowing argon gas supply system make use of C++ under the environment of VC++6.0. The aim is ensure the argon rate of flow into steel ladle reposefully according to set value. Firstly, it introduced the model selection of hardware and the design of simulation ladle. The system has a well human-computer interface.Its fuction includes set flow, dynamic curve display real time data and save real time data. Then did the water model experiment using physical sumulation on the basis of the system. It carries out optimization research to mixing effect at different agron flowrate, different air brick number and different arrange. At last, found the technological parameter what better effect of argon stirring and little mixing time to instructive to active producton mixing time.

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