Study And Development Of Optimizing Control System For The Ball Mill

This paper pointed out existing major problems of measurement, control and optimization of ball mill pulverizing system, which focused on system design of control system, optimizing algebra and model of grinding system. The following main parts were included in this thesis.Firstly, an hardware and software system were introduced which contained sampling, data processing and communication units. it introduced the current pulverizing system and its instrument and control system. Different control methods were compared in this part and air flow rate measurement was mentioned in this chapter.Secondly, some advanced control methods were discussed in this chapter. This part focused on optimizing algebra in experiment, which also discussed the main problem of current experiment method, the advantage of experiment for orthogonal design. Moreover, the main factors which influence the grinding efficiency were laid out by this method, and it found the basis of optimizing theme of pulverizing system.Thirdly, fault diagnosis was the main sub system of ball mill optimizing system. A fault diagnosis model based on neural network was introduced in this part. Specific samples which exemplified pulverizing system's operating status were chosen and trained.Lastly, the on-line coal_powder fineness monitoring was an unresolved problem in power plant. In this part and on-line measuring model was introduced based on neural network. This model was proved to be correct and feasible according to the coal_powder fineness test in a certain power plant.Generally speaking, this thesis combine theory with engineering field. Some new ideas were put forward in measuring, control and optimization.