Research Of Refining Furnance Bottom Blowing Argon Neural Networks PID Control And Optimize

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.