模糊聚类下气动阀门粘滞检测方法的改进

郑丽丽; 王志国; 刘飞

doi:10.13433/j.cnki.1003-8728.2018.0222

模糊聚类下气动阀门粘滞检测方法的改进

doi: 10.13433/j.cnki.1003-8728.2018.0222

1.
江南大学轻工过程先进控制教育部重点实验室, 江苏无锡 214122

基金项目:

国家自然科学基金项目（61134007）资助

详细信息

作者简介:
郑丽丽(1988-),硕士研究生,研究方向为阀门粘滞故障的检测与补偿,953913272@qq.com

通讯作者:
刘飞,教授,博士生导师,fliu@jiangnan.edu.cn

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- 文章访问数: 253
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- PDF下载量: 4
- 被引次数: 0
出版历程
- 收稿日期: 2016-12-22
- 刊出日期: 2018-02-25

Improved Detection of Pneumatic Control Valve Stiction using Fuzzy Clustering

1.
Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Jiangnan University, Jiangsu Wuxi 214122, China

摘要

摘要: 在工业过程控制中，气动阀门的粘滞非线性特性会导致控制回路性能下降甚至振荡。针对已有基于模糊聚类的阀门粘滞检测方法在故障检测过程中容易出现错误诊断问题，提出了改进方法，能有效识别外部干扰和阀门粘滞。首先利用模糊聚类算法对回路日常运行数据进行聚类分析得到聚类中心，根据粘滞阀门输入输出数据的分布特性，评价聚类中心的线性拟合度。然后对聚类中心所构成四边形进行凹凸性识别，再根据聚类中心的分布特征定义了一种新粘滞指标。通过给出的仿真实验，以及化工厂的两个流量控制回路故障检测实验，验证了所提方法的有效性和准确性。
- 气动阀门 /
- 粘滞非线性 /
- 模糊聚类 /
- 故障检测 /
- 凹凸性
Abstract: In the process industry, stiction nonlinearity existing in pneumatic control valve will lead to performance deterioration even oscillation in the control loops. Since the existing methods using fuzzy clustering algorithm may easily make wrong diagnosis in the detection, an improved method was proposed in this paper, which can effectively recognize the external disturbance and valve stiction. Firstly, the routine operating data were clustered using fuzzy clustering algorithm to obtain cluster centers and the goodness-of-fit was evaluated according to the distribution characteristic of sticky valve input-output data. The convex-concave property recognition of the quadrilateral formed by cluster centers was taken. On basis of the distribution of cluster centers, a new stiction index was defined. The simulations and two flow control loops of chemical industry were used to verify the validity and veracity of the improved method.
- pneumatic control valve /
- stiction nonlinearity /
- fuzzy clustering algorithm /
- fault detection /
- convex-concave property

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参考文献(19)

[1]	刘丽兰,刘宏昭,赵会荣,等.机械系统中粘滑摩擦研究进展[J].机械科学与技术,2016,35(5):662-671 Liu L L, Liu H Z, Zhao H R, et al. Review on stick-slip friction in Mechanical system[J]. Mechanical Science and Technology for Aerospace Engineering, 2016,35(5):662-671(in Chinese)
[2]	Hägglund T. A control-loop performance monitor[J]. Control Engineering Practice, 1995,3(11):1543-1551
[3]	Ender D B. Process control performance:not as good as you think[J]. Control Engineering, 1993,40(10):180-190
[4]	宋运忠,刘向龙.基于数据驱动的控制阀粘滞特性量化研究[J].控制工程,2016,23(8):1254-1260 Song Y Z, Liu X L. Quantification research on stiction of control valve based on data driven[J]. Control Engineering of China, 2016,23(8):1254-1260(in Chinese)
[5]	Di Capaci R B, Scali C, Pannocchia G. System identification applied to stiction quantification in industrial control loops:a comparative study[J]. Journal of Process Control, 2016,46:11-23
[6]	Horch A. A simple method for detection of stiction in control valves[J]. Control Engineering Practice, 1999,7(10):1221-1231
[7]	Horch A, Isaksson A J. Detection of valve stiction in integrating processes[C]//Proceedings of 2001 European Control Conference (ECC). Porto, Portugal:IEEE, 2001:1327-1332
[8]	Yamashita Y. An automatic method for detection of valve stiction in process control loops[J]. Control Engineering Practice, 2006,14(5):503-510
[9]	Rossi M, Scali C. A comparison of techniques for automatic detection of stiction:simulation and application to industrial data[J]. Journal of Process Control, 2005,15(5):505-514
[10]	He Q P, Wang J, Pottman M, et al. A curve fitting method for detecting valve stiction in oscillating control loops[J]. Industrial & Engineering Chemistry Research, 2007,46(13):4549-4560
[11]	Hägglund T. A shape-analysis approach for diagnosis of stiction in control valves[J]. Control Engineering Practice, 2011,19(8):782-789
[12]	李晨.控制回路的性能监控、诊断与改善[D].上海:华东理工大学,2015 Li C. Control loop performance monitoring, diagnosis and improvement[D]. Shanghai:East China University of Science and Technology, 2015(in Chinese)
[13]	Choudhury M A A S, Jain M, Shah S L. Stiction-definition, modelling, detection and quantification[J]. Journal of Process Control, 2008,18(3-4):232-243
[14]	陶巍.调节阀迟滞的检测与量化[D].上海:东华大学,2013 Tao W. The detection and quantification of the valve stiction[D]. Shanghai:Donghua University, 2013(in Chinese)
[15]	Daneshwar M A, Noh N M. Detection of stiction in flow control loops based on fuzzy clustering[J]. Control Engineering Practice, 2015,39:23-34
[16]	Choudhury M A A S, Thornhill N F, Shah S L. Modelling valve stiction[J]. Control Engineering Practice, 2005,13(5):641-658
[17]	汪庆淼.基于目标函数的模糊聚类新算法及其应用研究[D].江苏镇江:江苏大学,2014 Wang Q M. Research of new fuzzy clustering algorithms based on objective function and its applications[D]. Jiangsu Zhenjiang:Jiangsu University, 2014(in Chinese)
[18]	宋晓眉,程昌秀,周成虎.简单多边形顶点凹凸性判断算法综述[J].国土资源遥感,2011,(3):25-31 Song X M, Cheng C X, Zhou C H. An analysis and investigation of algorithms for identifying convexity-concavity of a simple polygon[J]. Remote Sensing for Land & Resources, 2011,(3):25-31(in Chinese)
[19]	International Database of Industrial Control Loops from Different Fields. International stiction data base[EB/OL]. 2013-08 https://sites.ualberta.ca/~bhuang/Stiction-Book/