论文部分内容阅读
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 measurement is an emerging industrial technology that constructs models based on modern estimation theory to deduce variables that are difficult to detect in engineering. This paper presents a soft-sensing technique based on Radial Basis Function Neural Network (RBFNN), and studies its application in soft measurement of light-oil freezing point based on the correlation between process mechanism analysis and process data. The results show that the good non-linear dynamic modeling ability of RBFNN makes it have great potential in soft-sensing.