神经网络在水泥生料配料中的应用

水泥生料配料系统具有多变量、大滞后和非线性的特点 ,采用传统的配料调优方法很难见效。人工神经网络具有很强的非线性映射、特征抽取和容错能力 ,为解决这类问题提供了新的思路。文章根据水泥生料配料的工艺要求 ,采用BP算法建立起能够较好地预测水泥生产质量的神经网络模型 ,以实现生料配料的调优操作。

Application of Neural Network in Cement Raw Materials Blending System

The cement raw materials blending system is very complex for its multi-variable, long time delay and nonlinear characters. It is difficult to set up an exact mathematic model with conventional optimum me-(thods.) Artificial neural Networks are able to give new solutions to such problems due to their capacities of nonlinear mapping, character take-out and error tolerance. According to technical requirements of cement raw materials blending, this paper applied neural network model based on BP algorithm to pre-estimate the quality of cement, to realize the optimization of cement raw materials.