摘要
催化剂积碳量是重整催化过程的重要指标,常规方法无法直接测量,辽阳石化分公司针对1.40Mt/a连续重整装置开发了基于RBF神经网络的催化剂积碳量软监测技术,并在联合装置DCS上得到应用。在简单介绍重整反应工艺的基础上,概括了重整催化剂积碳量软测量技术,阐述了RBF神经网络的理论基础,并进一步说明了催化剂积碳量软测量神经网络模型的建立,同时叙述了神经网络模型在DCS中的编程及软测量技术的实现。
Carbon deposition is an important index of reforming catalyst. It can＇t be directly measured with routine methods. Soft measurement technology for carbon deposition of reforming catalyst based on RBF neural network is developed for 1.40 Mt/a continuous reforming installation for Petrochina Liaoyang Company, and is applied in I）CS for integrated installation. On the basic of introducing reforming reaction progress simply, soft measurement technology on carbon deposition of reforming catalyst is outlined. RBF neural network theory is expounded. Establishment of neural network model for soft measurement of carbon deposition of catalyst is described further. Programming of neural network model in DCS and realization of soft measurement technology are described.
出处
《石油化工自动化》
CAS
2015年第3期29-32,共4页
Automation in Petro-chemical Industry
关键词
重整
催化剂
软测量
RBF神经网络
reforming
catalyst
soft measurement
RBF neural network
