Further study on Kano’s model and detection method for pneumatic valve stiction

HE Xiongxiong; ZOU Tao; YANG Yue; LI Xin

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Further study on Kano’s model and detection method for pneumatic valve stiction

更新时间：2025-12-10

- Further study on Kano’s model and detection method for pneumatic valve stiction
- CIESC Journal Issue 7, Pages: 1691-1697(2008)
- 作者机构：
  
  1. 浙江工业大学信息与控制研究所
  2. 丹佛斯（上海）自动控制有限公司
  3. 泰雷兹软件系统上海有限公司
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Online First：05 July 2008，
  
  Published：05 July 2008
- 稿件说明：
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HE Xiongxiong, ZOU Tao, YANG Yue, et al. Further study on Kano’s model and detection method for pneumatic valve stiction[J]. CIESC Journal, 2008, (7): 1691-1697.
DOI：

HE Xiongxiong, ZOU Tao, YANG Yue, et al. Further study on Kano’s model and detection method for pneumatic valve stiction[J]. CIESC Journal, 2008, (7): 1691-1697. DOI：

摘要

气动阀门的静摩擦现象在工业过程的控制中非常普遍，易引起控制系统的波动，从而影响生产的正常进行。在众多的研究成果中，Kano提出的气动阀门静摩擦模型与检测方法是简单有效的。但是，Kano气动控制阀静摩擦模型存在着不足，本文指出了该模型的缺陷所在，并给出了改进方案，使得模型的输入输出与物理过程完全一致；针对控制阀静摩擦的统计检测方法参数较多的特点，系统分析了影响检测结果的因素，总结了检测参数的指导原则。最后，在Matlab Simulink平台下编制了能够描述阀门静摩擦现象的S-Function模块，并进行了模拟仿真，在扰动存在的条件下讨论了统计检测方法的有效性。

Abstract

Pneumatic control valves stiction is very common in process industry. A big fluctuation of process will be caused by stiction and productivity will also be lowered. Among lots of research results

the method of describing stiction of pneumatic control valves and detecting stiction developed by Kano is simple and effective. However

some defects in the Kano’s method are pointed out by the authors. The model structure of pneumatic control valve of Kano was improved to overcome the existing defects so that the input and output were consistent with the physical process. To deal with multiple parameters in the statistical detection method

guide rules were presented through the analysis of the factors that affected the detection results. Finally

the stiction phenomenon was compiled to a module by using the S-function technology in Matlab Simulink. Simulation was made under the Matlab Simulink framework and the statistical detection method under disturbance was discussed.

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