Research On Ball Mill Control Optimization Based On Fuzzy Control Strategy

The intermediate ball mill coal pulverizing system is the common coal pulverizing system in the large and middle coal fired power companies of our company. The coal pulverizing system can not be controlled automatically for a long time because of that the data that be controlled of the system are nonlinearity, strongly coupled and the coal quantity in the ball mill can not be measured. In this text we design a system based on fuzzy control and neural network theory, the experience of the coal pulverizer’s operatol, The#7generating set in Datang International in Douhe Power Plant Coal Pulverizing System and design the system. The running condition of milling system varies all the time and the changes are very great, so it can not run under the economical working condition stably and the power consumption of pulverizing unit coal is high. Sometimes the coal mill runs empty or leaks coal dust so it results in huge waste and pollutes environment. In order to solve the problems of pulverizing control system such as high energy consumption and can’t run stably we imported MECS pulverizing optimization system form Shijiazhuang Development District Tianneng Science and Technology Ltd. MECS pulverizing optimization system is self-learning control system that was designed according to the characteristics of The ball type pulverizing system such as nonlinearity, large delay, strong coupling and multiple-input multiple-output. MECS pulverizing optimization system combines the traditional control theory with modern control theory, make use of graphic configuration mode and it applies the fuzzy control, expert control, neural network control to the practical control system. The application proved that the MECS pulverizing optimization system can assure the coal fineness and at the same time it can reduce the unit power consumption of coal pulverizing greatly. And it has energy saving and consumption reduction effect when the boiler burning stably.