|本期目录/Table of Contents|

[1]胡瑾秋,张来斌,伊岩,等.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.[doi:10.11731/j.issn.1673-193x.2016.10.013]
 HU Jinqiu,ZHANG Laibin,YI Yan,et al.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.[doi:10.11731/j.issn.1673-193x.2016.10.013]
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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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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
12
期数:
2016年10期
页码:
81-85
栏目:
现代职业安全卫生管理与技术
出版日期:
2016-10-30

文章信息/Info

Title:
Research on dynamic alarm management method of refining device based on Bayesian estimation
作者:
胡瑾秋张来斌伊岩蔡爽
(中国石油大学(北京)机械与储运工程学院,北京 102249)
Author(s):
HU Jinqiu ZHANG Laibin YI Yan CAI Shuang
College of Mechanical and Transportation Engineering, China University of Petroleum - Beijing, Beijing 102249, China
关键词:
贝叶斯估计过渡过程告警管理炼化装置
Keywords:
Bayesian estimation transient process alarm management refining device
分类号:
X937
DOI:
10.11731/j.issn.1673-193x.2016.10.013
文献标志码:
A
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。
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.

参考文献/References:

[1]赵宝生.云南电网计算机监视系统[J].电力系统自动化,1982(5):46-52. ZHAO Baosheng. Computer monitoring system for a power network in southwest China[J], Automation of Eletric Power Systems, 1982(5):46-52.
[2]赵彩明,郝立人.郑州供电网的调度计算机监控系统[J].电力技术,1982(6):78. ZHAO Caiming, HAO Liren. A computer monitor system for city network dispatching[J], Automation of Eletric Power Systems, 1982(6):78.
[3]汤胤,彭宏,郑启伦.一个基于范例推理的时序预测模型[J].计算机科学,2004,31(8):103-106. TANG Ren, PENG Hong, ZHENG Qilun. A case-based model for time series extrapolation[J], Computer Science, 2004,31(8):103-106.
[4]董辉,侯俊敏,傅鹤林,等.基于范例推理的公路隧道拱顶变形时序支持向量机外延预测[J].岩土力学,2011 (7):2099-2105. DONG Hui, HOU Junmin, FU Helin, et al. Support vector machine extrapolation prediction of tunnel arch- top deformation time series based on case-based reasoning[J]. Rock and Soil Mechanics, 2011(7):2099- 2105.
[5]李彤岩,肖海林,李兴明.通信网告警加权关联规则挖掘算法的研究[J].电子科技大学学报,2008,37(6):807-810. LI Tongyan, XIAO Hailin, LI Xingming. Algorithm for mining weighted alarm association rules in telecommunication networks[J]. Journal of University of Electronic Science and Technology of China, 2008,37(6):807-810.
[6]姚浩,李鹏,郭晓斌,等.基于大数据的告警信息处理和故障设备定位技术研究[J].电网与清洁能源,2014 (12):72-77. YAO Hao, LI Peng, GUO Xiaobin, et al. Research on alarm information disposal and fault device location based on mass data[J]. Power System and Clean Energy, 2014(12):72-77.
[7]李怡萌,顾雪平,李扬.电网故障的动态连续诊断方式[J].北京交通大学学报,2014(5):142-146. LI Yimeng, GU Xueping, LI Yang. Research on dynamic continuous diagnosis mechanism of power system faults[J]. Journal of Beijing Jiaotong University, 2014(5):142-146.
[8]F. Yang, S.L. Shah, D. Xiao, et al. Improved correlation analysis and visualization of industrial alarm data. ISA Transactions, 2012, 51(2012):499-506.
[9]Sandeep R. Kondaveeti, Iman Izadi, Sirish L. Shah, et al. Quantification of alarm chatter based on run length distributions[J]. Chemical Engineering Research and Design, 2013, 91(2013):2550-2558.
[10]Jason C. Laberge, Peter Bullemer, Mischa Tolsma, et al. Addressing alarm flood situations in the process industries through alarm summary display design and alarm response strategy[J]. International Journal of Industrial Ergonomics, 2014, 44(2014):395-406.
[11]Neminath Hubballi, Vinoth Suryanarayanan, Flase alarm minimization techniques in signature-based intrusion detection systems: A survey. Computer Communications, 2014, 49(2014):1-17.
[12]Arief Adhitya, Siew Fun Cheng, Zongda Lee, et al. Quantifying the effectiveness of an alarm management system through human factors studies[J]. Computers and Chemical Engineering, 2014, 67 (2014):1-12.
[13]Di Peng, Xiangbai Gu, Yuan Xu, et al. Integrating probabilistic signed digraph and reliability analysis for alarm signal optimization in chemical plant[J]. Journal of Loss Prevention in the Process Industries, 2015, 1 (33):279-288.

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备注/Memo

备注/Memo:
国家自然科学基金资助(51574263);中国石油大学(北京)科研基金资助(2462015YQ0403)
更新日期/Last Update: 2016-11-30