油气站场关键参数预测预警及安全导航技术研究与应用
Research and Application of Key Parameter Prediction and Early-warning and Safety Navigation Technology for Oil and Gas Stations
韩小磊1
作者信息
- 1. 中石化石油工程设计有限公司,山东东营 257026
- 折叠
摘要
为保障油气站场工艺平稳性,提前预判并解决可能出现的工艺参数异常,基于长短记忆神经网络算法开发了预测预警及安全导航系统.介绍了该系统的设计方案,分析了油气站场的工艺流程,阐述了关键生产参数的选取,以及预测预警模型和工艺安全导航专家逻辑库的建立.现场应用表明,该系统可以实现对油气站场关键生产参数的预测预警,提前给出关键参数的未来发展趋势,针对关键参数可能的超阈值异常情况,系统会自动提供专家安全指导策略,避免生产工艺进入故障状态.
Abstract
To ensure the processes stability of oil and gas station,and to predict and solve possible abnormity of process parameters in advance,a predictive early-warning and safety navigation system based on long short-term memory neural network algorithm has been developed.The design scheme is introduced.The process flow of the oil and gas station is analyzed.The selection of the key manufacture parameter and the prediction early-warning module and the construction of the process safety navigation system expert logical library are introduced.The practical application indicates that the system can predict early-warning of key production parameters in oil and gas stations.It can provide the future development trend of key production parameters in advance.For the case of possible exceeding threshold faults of key parameters,the system can automatically provide expert safety guidance strategies,and prevent processes from entering a fault status.
关键词
预测预警/安全导航/长短记忆神经网络模型/工艺平稳性Key words
prediction and early-warning/safety navigation/long short-term memory neural network model/process stability引用本文复制引用
出版年
2024
NETL
NSTL
万方数据