摘要
针对化工过程自控仪表设计与优化问题,提出了一种基于智能化算法的新方法。该方法综合利用了机器学习、深度学习等人工智能技术,通过对大量历史数据的挖掘分析,建立了精准的过程模型,并基于模型对控制策略进行了优化。仿真实验表明,该方法能够有效提升自控仪表的控制精度和响应速度,此外,还开发了一套自控仪表智能优化软件,实现了算法的工程化应用。
Aiming at the design and optimization of automatic control instruments in chemical processes,a new method based on intelligent algorithms is proposed.This method makes comprehensive use of artificial intelligence technologies such as machine learning and deep learning.By mining and analyzing a large amount of historical data,an accurate process model is established,and the control strategy is optimized based on the model.Simulation experiments show that this method can effectively improve the control accuracy and response speed of automatic control instruments.In addition,a set of intelligent optimization software for automatic control instruments is developed to realize the engineering application of the algorithm.
作者
陈欢
员一彬
Chen Huan;Yuan Yibin(Luoyang Ruize Petrochemical Engineering Co.,Ltd.,Luoyang,Henan,China,471000;Anhui Huadong Chemical and Pharmaceutical Engineering Co.,Ltd.Luoyang Branch,Luoyang,Henan,China,471000)
出处
《仪器仪表用户》
2024年第10期27-29,32,共4页
Instrumentation
关键词
化工过程
自控仪表
智能优化
机器学习
深度学习
chemical process
automatic control instrument
intelligent optimization
machine learning
deep learning
