基于改进BP神经网络的纸浆漂白MIMO软测量模型研究  

Research on soft measurement model of paper bleaching processbased on improved BP neural network

作　　者：唐德翠[1] 

机构地区：[1]广东技术师范学院自动化系,广州510635

出　　处：《工业仪表与自动化装置》2009年第3期54-56,共3页Industrial Instrumentation & Automation

摘　　要：针对漂白过程中纸浆白度、残氯在线测量的不足,提出基于BP改进算法的神经网络软测量模型。文章介绍了基于神经网络的软测量技术原理以及漂白软测量模型建立的步骤与方法,给出了该模型的仿真结果。仿真结果表明,该模型具有较高精度和准确性,为纸浆质量的评判和优化控制提供了指导作用。the soft measurement model of paper bleaching based on improved neural network is brought forward against the deficiency of brightness and remaining chlorine measurement online. The principle of soft measurement based on neural network is described and the steps and methods of modeling are introduced, finally, the results of simulation are given. The results show that the model is true and reliable and it helps to assessing paper quality and to optimizing control .

关 键 词：改进BP神经网络 白度和残氯 纸浆漂白 MIMO软测量 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]