Research And Optimization Of Temperature Uniformity And Process Parameters Of Roller Kiln

Roller kiln porcelain industry is a high energy consumption industry,which is the key industry of energy conservation and emission reduction in the world.Especially in China,in the context of national policy advocating green manufacturing and energy conservation and emission reduction and reduction of high energy consumption,reducing energy consumption has become a major target for the development and upgrading of roller kiln industry.Therefore,the optimization of energy consumption in the production process of ceramic enterprises has been paid more and more attention by ceramic enterprises.Because of the roller kiln is a one-off large investment industry,in view of existing production equipment companies,the cost of replacement kiln production line is extremely difficult to afford,so this article around the existing production equipment,according to the data obtained from the kiln production process and the means of numerical simulation is adopted to establish a simulation model based on existing equipment.There have been some researches on the simulation of roller kiln in China,but most of them focus on the structure of the kiln,the shape of the nozzle and other external design,and the research on temperature uniformity is not too much.At present,there are few studies on the influence law of process parameters on temperature uniformity of roller kiln,and it is very difficult to directly establish the functional relationship between process parameters and temperature.In view of this,BP neural network is selected in this thesis to realize the correlation between process parameters and temperature uniformity coefficient of roller kiln.Research method is through the simulation model using multiple sets of different production process parameters on the formula to obtain the process parameters and temperature distribution in the corresponding data,then the data by BP neural network to study training can get a quick response relationship between process parameters and temperature distribution network,at last,through genetic algorithm to get the optimal process parameters combination,and comparison analysis.The main contents of this paper are as follows:(1)Energy consumption analysis and modeling.In this paper,Through field data acquisition,some technological parameters of the production process were obtained,and the process of energy transfer and conversion in the production process of the roller kiln was studied and analyzed.It was concluded that the main effective energy consumption of the roller kiln was the energy consumption of the water evaporation of the embryo,the energy consumption of the decomposition of clay in the sintering process and the heat absorption in the sintering process of the embryo.The heat input is mainly the sensible heat brought into the fuel,and the fuel burns exothermic.The energy consumption model is established according to the above energy flow process.(2)Establishment of finite element simulation model.In this thesis,according to the design of a certain type of kiln,the structure of the roller kiln,material properties parameters,production process parameters and other information were obtained,and then the numerical simulation model of the firing section of the roller kiln was established based on fluent finite element calculation software.The physical property parameters of the structure and materials were set as fixed parameters,and the uniformity coefficient of temperature field under different process formulations was obtained by adjusting the values of natural gas flow,combustion-supporting air temperature,combustion-supporting air flow and flue gas flow in the production process parameters.The influence of these four parameters on temperature uniformity was obtained by orthogonal experiment.(3)Establish a multi-objective optimization model.BP neural network was used to study and train the data obtained from the orthogonal experiment to obtain a network that could quickly respond to process parameters and temperature uniformity,and then a genetic algorithm aiming at the optimal temperature uniformity coefficient and thermal efficiency was established to obtain the optimal formula of process parameters.