Research On Calcining Process Modeling And Control System In Rotary Kiln

In our country,cement has the characteristics of a wide use range and a large usage,cement is one of the most important raw material in the construction industry.Cement rotary kiln is one of the vital equipment during the whole production line.It is a large equipment for continuous high temperature works.Complex physical and chemical reactions occur simultaneously in rotary kiln and three phases of gaseous,liquid,and solid phase coexist.The rotary kiln is a complex system with multiple variables and the variables interact with each other.The condition of its operation directly influences the quality and output of the cement clinker,as well as energy consumption and environmental pollution.For a long time,cement production is mainly based on manual experience to control rotary kiln temperature.The backward manual operation leads to excessive energy consumption.Therefore,the specific research contents of this paper are as follows:In this paper,the mechanism model of rotary kiln is established.The corresponding mechanism model is established by analyzing the calcining process of the raw cement and the main parameters that can affect the temperature of the rotary kiln firing zone.During continuous calcination,some parameters are not fixed and change with temperature and pressure.If these parameters are always regarded as constants,the model can describe rotary kiln system,but the accuracy of system needs to be improved.A temperature soft sensor model is established.The model is established by using kernel principal component analysis technology to process the data and inputting the quantized filtered data.According to the model,a simulation experiment is designed.It can be seen from the simulation results that the soft measurement model accuracy is higher,which can obtain accurate and stable rotary kiln roasting temperature signals.Bayesian network is used to identify abnormal working conditions.By selecting the main influencing factors and using the algorithm to study the data structure,the Bayesian network diagnosis model is obtained.The algorithm is used in parameter learning.Finally,the posterior probability of the problem node is calculated to find out the cause of the abnormal temperature in the burning zone.A fuzzy PID controller is built.It is designed by studying the fuzzy control algorithm and optimizing parameters in detail.The temperature model of rotary kiln is simulated in this paper and the experimental results show that this method has better control effect.Finally,the realization method of the fuzzy PID algorithm is given.It provides a reference for the cement production industry in the future.