Stiction Quantification based on Time and Frequency Domain Criterions

Abstract Valve stiction is one of the most common causes for poor performance in industrial control loops. Therefore, a non-invasive method which can detect and quantify stiction is urgently needed in the process industry. Most of the current stiction estimation methods use time domain criterion, e.g. Mean Square Error, to jointly identify the stiction and process model parameters. However, stiction induced oscillation is a phenomenon which has some specific characteristics in the frequency domain. Thus, extracting frequency domain information in the routine operation data will provide a more reliable and accurate stiction estimation. In this work, under the framework of Hammerstein model identification and global optimization, a new stiction quantification method based on time and frequency domain criterions is proposed. Several simulation case studies are demonstrated to validate the proposed method.

[1]  Jin Wang,et al.  Valve Stiction Quantification Method Based on a Semiphysical Valve Stiction Model , 2014 .

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

[3]  John W. Cox,et al.  A practical approach for large-scale controller performance assessment, diagnosis, and improvement , 2003 .

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

[5]  W. L. Bialkowski.  Dreams versus reality: a view from both sides of the gap: manufacturing excellence with come only through engineering excellence , 1993 .

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

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

[8]  Jiandong Wang,et al.  Detection of asymmetric control valve stiction from oscillatory data using an extended Hammerstein system identification method , 2014 .

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

[10]  Raghunathan Rengaswamy,et al.  Stiction identification in nonlinear process control loops , 2010, Comput. Chem. Eng..

[11]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[12]  Tore Hägglund,et al.  Detection and Diagnosis of Oscillation in Control Loops , 1997 .

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

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

[15]  Nina F. Thornhill,et al.  Control Loop Performance Assessment for Power Plants , 2006 .

[16]  Celso J. Munaro,et al.  Quantification of Valve Stiction and Dead Band in Control Loops Based on the Harmonic Balance Method , 2012 .

[17]  Claudio Garcia,et al.  Valve friction and nonlinear process model closed-loop identification , 2009 .