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 .
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
关键词
改进BP神经网络
白度和残氯
纸浆漂白
MIMO软测量
improved BP neural network
brightness and remaining chlorine
paper bleaching
MIMO soft measurement
