摘要
裂解炉是乙烯装置的核心设备,裂解炉控制的品质不仅影响乙烯和丙烯的收率,而且会直接影响后续单元的平稳操作。运用神经网络技术建立了裂解深度预测模型,开发并实施了基于Smith预估控制的裂解炉裂解深度先进控制系统,减少了油品属性波动造成的影响,稳定了裂解深度,提高了乙烯装置的稳定性和乙烯、丙烯的收率。
Cracking furnace is the core installation for ethylene unit.control quality of the cracking furnace influences not only the yield of ethylene and propylene,but also the stable operation for the consequence unit.The cracking depth predictive model is established using neural network technology.Advanced process control system for the cracking depth of cracking furnace based on Smith prediction control is developed and implemented.The impact of oil property fluctuation is overcome.The cracking depth is stabilized.The ethylene installation stability and the yield of ethylene and propylene are improved.
作者
苏耀东
刘鉴徵
Su Yaodong;Liu Jianzheng(Sinopec Qilu Petrochemical Company,Zibo,255434,China)
出处
《石油化工自动化》
CAS
2019年第1期45-48,共4页
Automation in Petro-chemical Industry
关键词
神经网络
裂解深度
先进控制
裂解炉
模型
neural network
cracking depth
advanced process control
cracking furnace
model
