基于人工神经网络的中速磨存煤量软测量方法

中速磨直吹式制粉系统是火力发电厂锅炉运行稳定的一个重要环节，其磨机内存煤量能否获得可靠监测对发电厂的自动控制、经济运行和安全生产均有十分重要的意义。通过基于工艺机理知识，分析了中速磨直吹式制粉系统筒内存煤量的各相关因素，提
出了利用人工神经网络进行存煤量软测量的方法，给出了基于BP 改进算法的回归神经网络与延时神经网络综合模型，为中速磨存煤量的检测提供了新方法。离线训练与计算机仿真结果证实了软测量方法的可行性。
关键词：中速磨煤机 存煤量 软测量 改进算法
Abstract：Powdered system of straight blow medium speed mills is one of the important sections in fossil-fired power plants. Reliable monitoring for the quantity of reserving coal in the mills is significant to automation control，economical operation and safe production. Based on the knowledge of technique mechanism，various related factors to the quantity of reserving coal are analyzed. The method of soft-sensing by using artificial neural network is proposed and the integrated model of regressive neural network and time delay neural network based on BP improved algorithm are given. This provided a new method for detecting the reserving coal for medium speed mills. Through off-line training and computerized simulation，the results prove that the soft-sensing method is feasible.
Keywords：Medium speed mill Quantity of reserving coal Soft-sensing Improved algorithm