基于数据驱动的化工过程参数报警阈值优化

doi:10.3969/j.issn.0438-1157.2012.09.010

化工学报 ›› 2012, Vol. 63 ›› Issue (9): 2733-2738.DOI: 10.3969/j.issn.0438-1157.2012.09.010

基于数据驱动的化工过程参数报警阈值优化

刘恒, 刘振娟, 李宏光

北京化工大学信息科学与技术学院, 北京 100029

收稿日期:2012-06-05 修回日期:2012-06-11 出版日期:2012-09-05 发布日期:2012-09-05
通讯作者: 李宏光
作者简介:刘恒(1985-),男,硕士研究生。

A data-driven approach to chemical process alarm threshold optimization

LIU Heng, LIU Zhenjuan, LI Hongguang

College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China

Received:2012-06-05 Revised:2012-06-11 Online:2012-09-05 Published:2012-09-05

摘要/Abstract

摘要： 为了提高化工过程报警系统的性能,需要对过程参数的报警阈值进行优化设置。针对传统阈值方法存在的问题,采用核密度估计方法、基于历史数据对过程报警状态进行估计,从最小化误报警和漏报警概率的角度建立了优化过程报警阈值的目标函数,并采用数值优化的方法进行求解。应用于TE过程的仿真结果表明,此方法能够有效地减少过程误报警的次数,并且对漏报警的次数进行抑制。

关键词: 过程报警, 阈值, 优化, 核密度估计

Abstract: In order to improve the performance of chemical process alarm systems,it is imperative to optimize assignments of process alarm thresholds.In response to limitations of traditional threshold assignment methods,based on historical data,this paper firstly invokes kernel density estimation methods to identify process alarm states before an objective associated with alarm threshold optimization in terms of minimizing the probabilities of false and missed alarms is established along with enabling numerical solvers.Simulation results on TE process demonstrate that the proposed approaches can effectively reduce the number of false alarms as well as limit that of missed alarms.

Key words: process alarms, thresholds, optimization, kernel density estimation

中图分类号:

TP277

刘恒, 刘振娟, 李宏光. 基于数据驱动的化工过程参数报警阈值优化[J]. 化工学报, 2012, 63(9): 2733-2738.

LIU Heng, LIU Zhenjuan, LI Hongguang. A data-driven approach to chemical process alarm threshold optimization[J]. CIESC Journal, 2012, 63(9): 2733-2738.

参考文献 17

[1]	Shahriari M,Shee A,Ortengren R.The development of critical criteria to improve the alarm system in the process industry[J].Human Factors and Ergonomics in Manufacturing,2006,16(3):321-337
[2]	Bristol E H.Improved process control alarm operation[J].ISA Transactions,2001,40:191-205
[3]	Bransby M L,Jenkinson J.Alarm management in the chemical and power industries:results of a survey for the HSE//IEE Colloquium on Stemming the Alarm Flood.London,1997
[4]	Brown D C.Alarm management experience in BP oil//IEE Colloquium on Stemming the Alarm Flood.London,1997
[5]	Foong O,Suziah,Rohaya D,Syazwani N.ALAP:alarm prioritization system for oil refinery//Proceedings of the World Congress on Engineering and Computer Science.San Francisco,2009
[6]	Izadi I,Shah S L,Shook D S,Chen T.An introduction to alarm analysis and design//Proceedings of the 7th IFAC Symposium on Fault Detection Supervision and Safety of Technical Processes.Barcelona,2009:651-656
[7]	Wit J de.EEMUA recommendations for the design and construction of refrigerated liquefied gas storage tanks[J].Cryogenics,1998,28(12):800-804
[8]	Chao C S,Liu A C.An alarm management framework for automated network fault identification[J].Computer Communications,2004,27(13):1341-1353
[9]	Jiang R.Optimization of alarm threshold and sequential inspection scheme[J].Reliability Engineering and System Safety,2010,95:208-215
[10]	Mezache A,Soltani F.A novel threshold optimization of ML-CFAR detector in Weibull clutter using fuzzy-neural networks[J].Signal Processing,2007,87:2100-2110
[11]	Verdier G,Hilgert N,Vila J P.Adaptive threshold computation for CUSUM-type procedures in change detection and isolation problems[J].Computational Statistics and Data Analysis,2008,52:4161-4174
[12]	Brooks R,Thorpe R,Wilson J.A new method for defining and managing process alarms and for correcting process operation when an alarm occurs[J].Journal of Hazardous Materials,2004,115:169-174
[13]	Chen J.On reducing false alarms in multivariate statistical process control[J].Chemical Engineering Research and Design,2010,88:430-436
[14]	Zhu Hengwei(朱恒伟),Wang Kechang(王克昌),Chen Qizhi(陈启智).Adaptive thresholds algorithm for fault detection of liquid rocket engine in ground test[J].Journal of Propulsion Technology(推进技术),2000,21(1):1-4
[15]	Yu Chuanqiang(于传强),Guo Xiaosong(郭晓松).Slide bandwidth kernel density estimation algorithm based on estimate point [J].Acta Armamentarii(兵工学报),2009,30(2):231-235
[16]	Bian Zhaoqi(边肇奇),Zhang Xuegong(张学工).Pattern Recognition(模式识别)[M].Beijing:Tsinghua University Press,2000
[17]	Downs J J,Vogel E F.A plant-wide industrial process control problem[J].Computers Chem. Engng.,1993,17(3):245-255

基于数据驱动的化工过程参数报警阈值优化

A data-driven approach to chemical process alarm threshold optimization

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