摘要
软测量是一门新兴的工业技术，它借助现代估计理论构造模型推断出工程上难以检测的变量。本文提出了基于径向基函数神经网络（RBFNN）的软测量技术，并且结合工艺机理分析和过程数据关联，对其在轻柴油凝固点软测量的应用进行了研究。结果表明，RBFNN的良好的非线性动态建模能力使其在软测量中具有很大的应用潜力。
Soft-sensing is a newly-developed industrial technique which by means of modem modelling technique can provide inferences of variabes hard to be measured. In this paper, radial basis function neural networks (RBFNN )based soft-sensing is proposed. It, combining with the analysis of process principles and correlation of the process data, can be applied to the soft-sensing of the light cycles oil freeze point. The result shows that RBFNN has fine capability of nonlinear dynamic modelljng.
出处
《自动化与仪器仪表》
1998年第2期16-19,共4页
Automation & Instrumentation
关键词
测量技术
神经网络
温度
流量
压力
框图
软测量
Soft-Sensing Radial Basis Function Neural Network Dynamic Modelling
