| 基于贝叶斯估计的炼化装置动态告警管理方法研究 |
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| 引用本文： | 胡瑾秋,张来斌,伊岩,蔡爽.基于贝叶斯估计的炼化装置动态告警管理方法研究[J].中国安全生产科学技术,2016,12(10):81-85. |
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| 作者姓名： | 胡瑾秋 张来斌 伊岩 蔡爽 |
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| 作者单位： | (中国石油大学(北京)机械与储运工程学院，北京 102249) |
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| 摘 要： | 针对现有告警管理方法无法判断炼化装置运行中的过渡过程，对过渡过程不能进行准确有效地监测和管理，提出
了基于贝叶斯估计的动态告警线计算方法。通过训练历史过渡过程数据得到先验概率，自适应判断过渡过程和估计动态
告警线，解决了传统告警线的斜率不能赋值且只能依靠人为调节的问题，并可通过判断系统状态调节告警管理方式。经
常压塔原油进料流量调整和减压炉干气流量工艺调节的过渡过程现场数据验证，结果表明:与传统告警管理方法相比，
基于贝叶斯估计的动态告警管理方法的误告警总数量减少了87.34%，避免了告警洪水的发生，提高了炼化工艺运行的安
全性和可靠性。
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| 关 键 词： | 贝叶斯估计 过渡过程 告警管理 炼化装置 |
Research on dynamic alarm management method of refining device based
on Bayesian estimation |
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| HU Jinqiu,ZHANG Laibin,YI Yan,CAI Shuang.Research on dynamic alarm management method of refining device based
on Bayesian estimation[J].Journal of Safety Science and Technology,2016,12(10):81-85. |
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| Authors: | HU Jinqiu ZHANG Laibin YI Yan CAI Shuang |
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| Affiliation: | College of Mechanical and Transportation Engineering, China
University of Petroleum - Beijing, Beijing 102249, China |
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| Abstract: | Aiming at the problems that the existing alarm management methods can't judge the transient
processes when the refining device is operating, and they can't monitor and manage the transient
processes accurately and effectively, a calculation method of dynamic alarm line based on Bayesian
estimation was proposed. The prior probability was obtained by training the historical data of transient
processes, then the transient processes were adaptively judged, and the dynamic alarm line was
estimated. The problem that the slope of traditional alarm line can't be assigned and can only be
adjusted manually is resolved, and the alarm management mode can be adjusted through judging the system
status. Through field data verification of transient processes including flow adjustment on crude oil
feed in atmospheric tower and technical adjustment on dry gas flow in vacuum furnace, it showed that
compared with traditional alarm management methods, the total amount of error alarm by the dynamic alarm
management method based on Bayesian estimation reduced by 87.34%, which avoided the occurrence of alarm
flooding. |
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| Keywords: | Bayesian estimation transient process alarm management refining device |
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