Valve Stiction Quantification Method Based on a Semiphysical Valve Stiction Model

Valve stiction is one of the most common equipment problems that can cause poor performance in control loops. Consequently, there is a strong need in the process industry for noninvasive methods that can not only detect but also quantify stiction. In this work, on the basis of a physical and a semiphysical model, a new valve stiction signature is proposed. Industrial evidence is provided to validate the new valve stiction signature. Although valve stiction is a stochastic phenomenon that can not be exactly described by any deterministic model, the revised valve signature provides a better description of sticky valve behavior, particularly when valve stiction is severe. On the basis of the revised valve stiction signature, a noninvasive, simple, and robust valve stiction quantification method is proposed using the routine operation data and limited process knowledge. The proposed quantification method estimates the stiction parameters, namely, static friction and dynamic or kinetic friction, without requiring the valve position signal. Quantification is accomplished by using linear and nonlinear least-squares methods which are robust and easy to implement. The properties of the proposed algorithm are investigated using simulated case studies of first order plus time delay processes, and the performance of the method is compared to other stiction quantification methods using 20 industrial cases.

[1]  Vinay Kariwala,et al.  Confirmation of control valve stiction in interacting systems , 2009 .

[2]  Alexander Horch A simple method for detection of stiction in control valves , 1999 .

[3]  Sirish L. Shah,et al.  Stiction – definition, modelling, detection and quantification , 2008 .

[4]  S. Qin,et al.  A Curve Fitting Method for Detecting Valve Stiction in Oscillating Control Loops , 2007 .

[5]  Jorge Otávio Trierweiler,et al.  Valve stiction estimation using global optimisation , 2012 .

[6]  Ashish Singhal,et al.  A simple method for detecting valve stiction in oscillating control loops , 2005 .

[7]  Biao Huang,et al.  Stiction Estimation Using Constrained Optimisation and Contour Map , 2010 .

[8]  Damien Garcia,et al.  Robust smoothing of gridded data in one and higher dimensions with missing values , 2010, Comput. Stat. Data Anal..

[9]  Claudio Scali,et al.  Stiction Quantification: A Robust Methodology for Valve Monitoring and Maintenance Scheduling , 2014 .

[10]  Mohieddine Jelali,et al.  Estimation of valve stiction in control loops using separable least-squares and global search algorithms , 2008 .

[11]  Guy A. Dumont,et al.  Detection and diagnosis of oscillations in control loops , 1996, Proceedings of 35th IEEE Conference on Decision and Control.

[12]  Nina F. Thornhill,et al.  Detection and Diagnosis of Plant‐Wide Oscillations , 2008 .

[13]  Yoshiyuki Yamashita An automatic method for detection of valve stiction in process control loops , 2006 .

[14]  Sirish L. Shah,et al.  Modelling valve stiction , 2005 .

[15]  Raghunathan Rengaswamy,et al.  Control Loop Performance Assessment. 2. Hammerstein Model Approach for Stiction Diagnosis , 2005 .

[16]  Manabu Kano,et al.  Comparison of statistical process monitoring methods: application to the Eastman challenge problem , 2000 .

[17]  Mohieddine Jelali,et al.  Detection and Diagnosis of Stiction in Control Loops , 2010 .

[18]  Alexander Horch Condition Monitoring of Control Loops , 2000 .

[19]  Claudio Scali,et al.  A comparison of techniques for automatic detection of stiction: simulation and application to industrial data , 2005 .

[20]  Raghunathan Rengaswamy,et al.  Control loop performance assessment. 1. A qualitative approach for stiction diagnosis , 2005 .

[21]  Francis J. Doyle,et al.  Friction compensation for a process control valve , 2000 .

[22]  Nina F. Thornhill,et al.  Automatic detection and quantification of stiction in control valves , 2006 .