The Research On Control System For Temperature Of The Reaction Tower In Powdery-explosive Plant

Powerful and cheap powdery explosive is a very important energy source, which had been extensively used in many fields such as agriculture, water conservancy, traffic, mining and building materials. So the research and spread of continuous production technology of powdery explosive have become an intensive problem. Controlling the temperature of the reaction tower is one of the key processes in the process of powdery explosive production. The control is of important significance in improving the quantity and quality of product, decreasing energy consume and working intensity and ensuring safety production.The mechanic theory and characteristic of the production process are analyzed in this paper. Considering the characteristics of heat radiation that are nonlinearity, large inertia and time delay, this paper proposes a fuzzy neural network strategy to carry out the temperature control on the condition that the exact model of control object is hard to be build.Taking into account the factors to the temperature of reaction tower, suitable sense organs are adopted to build the monitoring system. At the same time, BP (Back Propagation) neural network is adopted to build a predicting model which can assist fuzzy logic controller carrying out the temperature control. By doing some simulation experiments, the effects from different control strategies are compared to prove the fuzzy neural network control system is practicable. The structure and function of temperature system are presented to make the system into reality. Some technologies such as data communication and database are used in the system.The fuzzy neural network control system on temperature of reaction tower is used in powdery explosive production process. The validity of this strategy is proved by the running results. The control system is stable and reliable. The temperature of reaction tower is effectively controlled. The continuous production is successfully realized. The quality is insured and quantity of the product is improved obviously.