摘要
随着制造行业智能化的发展,模拟计算大量应用于化工生产过程。本文利用混合建模技术设计了一套炼化装置智能操作优化软件,采用深度学习算法和遗传算法对模型进行优化。该软件能够实时预测产品质量、优化操作参数、进行数据预警。相比于传统的机理建模速度更快准确度更高,提高了炼厂操作过程的精细化程度、运行过程的稳定性以及生产过程的产品质量。
With the development of intelligent manufacturing industry,simulation calculation is widely used in chemical production process.This article used hybrid modeling technology to design a set of intelligent operation optimization software for refining and chemical equipment,and used deep learning algorithms and genetic algorithms to optimize the model.This software could predict product quality in real-time,optimize operating parameters,and provide data alerts.Compared to traditional mechanism modeling,it was faster and more accurate,could improve the refinement of the refinery operation process,the stability of the operation process,and the product quality of the production process.
作者
郝玉良
马时霖
马成详
苏然
陈爱军
刘浩
李秋蓉
Hao Yuliang;Ma Shilin;Ma Chengxiang;Su Ran;Chen Aijun;Liu Hao;Li Qiurong(Kunlun Digital Technology Co.,Ltd.,Beijing 102206,China;PetroChina Lanzhou Petrochemical Company,Lanzhou 730060,China;PetroChina Lanzhou Petrochemical Yulin Chemical Co.,Ltd.,Yulin 719199,China)
出处
《广东化工》
CAS
2024年第16期116-118,144,共4页
Guangdong Chemical Industry
关键词
深度学习
混合建模
实时优化
模拟计算
操作优化
deep learning
hybrid modeling
real-time optimization
simulation calculation
operation optimization