Research And Application Of Advanced Control Technology In Vacuum Induction Melting

Vacuum induction furnaces are important melting equipment, which are mostly used to produce Ni/Co based high temperature alloys, Ti alloys, stainless steels, super high-strength steels and special alloy materials. These special alloy materials have been found numerous applications in aviation, spaceflight navigation, arms industry, nuclear power and energy sources. As an important part in vacuum induction melting (VIM), the automatic control system has a direct influence on the quality and output of products. At present, for the laggard control techniques and the low-level automatization, the process control has become a key problem to restrict the development of vacuum induction furnaces. This task is supported by a main project of National Defense Science & Industry Committee in China. The application of advanced process control technology in VIM was studied in this paper. The main study achievements include: (1) Establishing model and process optimizing for VIMIn order to realize the system goal of quality stabilization and cost lowest and surround the two basis keys: temperature control and composition control, this paper advances an optimal method of process setting values during production. A model with conservation of energy was established on the basis of electro thermal equilibrium of system. Then the optimal electric power supply method was designed. The method provides theoretic foundation upon which practical power supply system is established. Using BP neural network a model of technology process in melting period of VIM was established. And the simulation was based on the data of practical industrial product process. The input and allocation of the electrical power in the melting period was optimized by Genetic Algorithm based on some steel. The simulation results show the effectiveness and advantage of the approach. The optimal temperature control is achieved by optimal power control and the composition control is perfected by optimal materials adding control. The whole optimization control algorithm possesses industrial validity and higher control precision, which resolves the state optimization control problem with multi-constrained, uncertain, nonlinear, characteristics.(2) The prediction and control for end-point temperature and end-point composition...