Research Of Neural Network Forecast System For Cement Clinker Calcination Quality

The cement clinker calcination is a complicated industry process which is nonlinear, greatly lagged, multi-variable and strongly disturbed. The forecast of cement clinker calcinations quality is very important to the optimization control of the produce process of cement. Because the require of forecast modeling for this complicated system is difficult to be satisfied by the traditional forecast methods, it is significant to apply artificial technology to build the neural network forecast system for the calcination quality of cement clinker.Through analyzing the calcination system of cement clinker, the scheme of neural network forecast, which include neural network system and data pretreatment system, is proposed; The method of data pretreatment, which is needed for neural network modeling and consist of cleaning data, switching data and selecting the variables of neural network, is researched; BP network model and BP algorithm are also researched and BP algorithm is improved by adding the momentum item and self-adapting the length of train step.A general system frame which can be used to develop complex software is built. A tool software for modeling neural network is developed on this software frame. A neural network forecast model of cement clinker calcination quality is built by this tool software. A good forecast result is got through this model: the relative error of g/L is 1.8%, the relative error of the content of f-CaO is 2.8%.