Abstract

It is known that the variable is strong coupling, nonlinear, multivariable and large time-delay dynamic characteristics in the raw cement vertical mill grinding process. Against the problem which is difficult to establish accurate mathematical model, this paper establishes a production index prediction model of vertical mill raw meal grinding process by using echo state network and Kalman Filter. And it's to use a cement plant raw cement vertical mill grinding process parameters to training and testing data of the model. After comparing with the BP neural network model, the experimental results show that the proposed modeling method is effective, and the raw cement vertical mill grinding process operation process stability has increased.

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