The Booster Production Line Temperature Control Design And Development Based On Neural Network PID

Booster is a new type of industrial explosives, which is an important role in mines’blasting in china, during the mines’ blasting operations various of blasting holes’ detonationneed use the booster to detonate, in modern society, the booster play a more and moreimportant role. Because of the important role in modern society’s construction，booster’squality is concerned by us. The research show that the booster which can detonate various ofinsensitive explosives has character of high performance and quality.The booster canimprove the blasting effect with low cost, insensitive explosives can not be detonatedcompletely by booster which have low quality and performance, blasting effect will beaffected and the cost will be increase, even can lead serious accident, such as the casualtiescaused by the misfire, it is a big waste of production and labor.The explosive velocity brisance and initiative sensitivity are the important indexs tomeasure the explosion transfer performance of the booster. measured by the productionprocess of the booster, temperature is a principal factor which influence the quality of booster,when the temperature is different, the explosive velocity、brisance and initiative sensitivityof the booster will be always different. in recent years, due to the requirements of boosterfrom Chinese and foreign market is still increasing, how to improve the production efficiencyand quality is the key to determine if the company can profit. At present, our production lineof the booster exist the objective factors such as low degree of automation and lowsecurity,which influence the export of the booster in some degree. so we need to improve theexisting production line of booster,primarily improve the quality of production by control thetemperature. This paper mainly research about improving the production line of Shandongtianbao chemicals plant, redesign a control scheme of the booster’s production line. Themain research contents are as follows:(1) Briefly analysis the process of booster’s manufacture at first,get a conclusion thatthe temperature is a main factor which influence the Booster’s quality,analysis the controlsystem’s characters of Booster, propose a method that apply the neural network controlalgorithm into the temperature control system of booster’s production line.(2) Describe the development of intelligent control and the theory of neural networkcontrol(3) Detailed analysis the process of producing booster, then analysis the process controlsystem which applied into the production line,propose a new control method according to the result---distributed control system at last.By analysis the temperature control system ofboosters’ production line and various of control algorithm, determine to use the BP-PIDwhich use the linear predictive model as the temperature controller.(4) After understand the control theory of BP-PID，design BP-PID controller to controlthe temperature of boosters’production line,set up the model and simulate it.(5) Programming realization of the neural network PID control algorithm on PC andPLC by using the Kingview software. this paper program the algorithm by C++language,build the dynamic link library(DLL),which is combined with the Kingview software andS7-300PLC programming software, make the programming structure of the neural networkPID algorithm to realize on the PC and PLC platform, namely to achieve it by differentprogram block.After completing the reform of booster’s production line, we have a one-day trial runand record the important parameters such as temperature. According to the recorder data, theobtained result of the control effect is ideal, because using the neural network PID controlalgorithm to control the temperature, the accuracy of booster’s temperature control isimproved,which meet the accuracy requirements of temperature’s control.