Research On Fault Diagnosis Of Cement Rotary Kiln Based On Intelligent Control Algorithm

Cement rotary kiln is an important equipment in the process of cement production,and it is also the key part of the new dry process cement technology which is widely used now.Therefore,the running condition of rotary kiln will directly affect the output,quality and energy consumption of the cement kiln.But the cement calcination which occurs in the rotary kiln involves many variables which are interrelated in a complex way,and the structure of the rotary kiln itself is very complex.So the fault diagnosis of rotary kiln is always very difficult.Therefore,the research on the fault diagnosis of rotary kiln is worthy of doing and beneficial to practice.Based on above,this paper proposes the research on the fault diagnosis of cement rotary kiln based on intelligent control algorithm.First of all,the improved selection operator of genetic algorithm is introduced due to slow convergence and local optimum problems of genetic algorithm.And it succeeds selecting better individuals of genetic algorithm and keeping the diversity of the population as well as improving the accuracy of the optimal solution in the global range.Secondly,the improved genetic algorithm is used to optimize the weights of back propagation neural network,and a neural network optimization algorithm based on improved genetic algorithm is proposed,The optimized back propagation neural network improves the convergence and convergence rate of the network by optimizing the initial weights and thresholds.And then,the steps of the cement production by rotary kiln are demonstrated.After that,the cement data variables are selected and the fault diagnosis of cement rotary kiln model based on neural network optimization algorithm based on improved genetic algorithm is built.And the fault diagnosis of cement rotary kiln is carried out with the proposed model and sensitivity analysis.Finally,a brief introduction about will have been used in production of particle swarm optimization algorithm of back propagation neural network model,and application of the algorithm in fault diagnosis model of cement rotary kiln is introduced,comparative analysis of the performance characteristics of neural network optimization algorithm based on improved genetic algorithm and particle swarm optimization algorithm of back propagation neural network model.