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Use Signal Characterization in the DCS to Linearize the Installed Flow Characteristic of a Valve

 

The following tip is from the ISA book by Greg McMillan and Hunter Vegas titled 101 Tips for a Successful Automation Career, inspired by the ISA Mentor Program. This is Tip #84.

 

Signal characterization to linearize valve installed flow characteristic has a bad reputation due to some practical implementation problems. These problems can be addressed today by doing the characterization in the distributed control system (DCS), but the stigma remains. With pneumatic positioners, signal characterization was done by the use of a cam. Standard cams were based on linearization of the inherent characteristic, when linearization of the installed flow characteristic is really required. Custom cams had to be cut for linearizing installed characteristics.

When a positioner was replaced in the middle of the night, the chances were marginal that the new positioner would have the right cam. Operators, Maintenance, and Process Technology did not like the fact that 50 percent output did not mean that the valve was 50 percent open. When a loop was in manual or when the valve needed to be stroke tested, the unknown relationship between controller output and valve position was not appreciated, to say the least. Even with the advent of digital positioners that enabled flexible and more precise adjustment of the installed characteristic, the confusion and lack of visibility in the control room remained. The other complaint was that signal characterization increased the effect of deadband.

 

For a change on the steep part of the installed characteristic, the change in control signal to the positioner was smaller. The change in signal could become less than the deadband. What was not realized is that for a change on the flat part of the installed characteristic, the change in signal becomes larger, reducing the effect of deadband. Also not recognized is that part of the solution was to get a better valve with less deadband. Furthermore, functionality can be added in the DCS to help deal with deadband as noted in the Control Talk blog Deadband and Resolution Limit Cycle Causes and Fixes. If the signal characterization is done in the DCS, all of these problems can be addressed.

A standard signal characterization block in the DCS enables a process control engineer to monitor and improve valve installed characteristic. The operator interface can include features to improve the visibility of what the valve is doing. Function blocks can be added to improve the response to small signal changes that occur when the valve is operating on the steep part of the characteristic. Adaptive tuning and gain scheduling can accomplish some of the linearization. However, the number of gain regions is limited to five, whereas a signal characterizer has 20 or more regions. Signal characterizer blocks can be cascaded to provide even greater resolution. By doing signal characterization, the adaptive tuner is freed to take care of process gain and split range nonlinearities.

Concept: The function blocks in a DCS can overcome most of the problems that originate from doing signal characterization in the field, which was particularly problematic in the days of pneumatic positioners with cams. Improvements in the control displays can provide the necessary visibility and understanding for operations and maintenance.

Details: Use a signal characterization block in the DCS to linearize valve flow response based on the installed flow characteristic. Control valve suppliers offer software to compute the installed flow characteristic. The signal characterizer input is the PID output (percent stroke on characteristic) and the characterizer output is the signal to the control valve (percent flow on characteristic). Space the XY pairs closer to provide more compensation in the areas of greatest nonlinearity.

If higher resolution is needed, cascade the signal characterization blocks. Use XY plots to show the installed nonlinear characteristic, the characterized linearized characteristic, and the relationship between PID output and linearized signal. Use a flow measurement synchronized with the valve signal to provide the operating point on an XY plot of flow versus PID output. Consider updating the installed characteristic during setpoint changes and start-up. Show the valve stroke next to the PID output on the PID faceplate. Use a deadband compensator or lead-lag block on the output of the signal characterization block to help get the signal through the deadband for operating points on the steep part of the installed characteristic.

 

Watch-outs: Fouling of piping and process equipment can dramatically increase the frictional losses in a system, reducing the ratio of valve drop to system drop. The installed characteristic slope of rotary valves, particularly butterfly valves, can be too flat above 60 percent open. Valves with a linear inherent characteristic display a quick opening installed characteristic, with a slope that is first too steep and then too flat for small valve drop to system drop ratios. Note that people sometimes mistakenly use the term hysteresis for backlash. The hysteresis in a valve response is the bowing of the stroke (maximum difference in stroke) between an increasing and a decreasing signal. The bowing is less than the deadband from backlash and is not as problematic in that the valve stroke will immediately reverse direction. For a valve with backlash, the signal has to go through a deadband to reverse stroke.

Exceptions: Valves with excessive stick-slip or a quick opening characteristic should be corrected first before being characterized. An equal percentage trim characteristic provides a valve gain proportional to flow that compensates for the process gain, which is inversely proportional to flow for concentration or temperature control of inline equipment (Tip #79). If the PID output goes directly to the control valve instead of to a flow controller, linearization of the valve by signal characterization is counterproductive. The installed characteristic may be unknown or too variable for linearization.

Insight: Signal characterization in a DCS can solve problems resulting from signal characterization in the valve positioner.

Rule of Thumb: Use signal characterization in a DCS to linearize the installed flow characteristic of a valve and free up the adaptive tuner for higher level functions.

 

About the Author
Gregory K. McMillan, CAP, is a retired Senior Fellow from Solutia/Monsanto where he worked in engineering technology on process control improvement. Greg was also an affiliate professor for Washington University in Saint Louis. Greg is an ISA Fellow and received the ISA Kermit Fischer Environmental Award for pH control in 1991, the Control magazine Engineer of the Year award for the process industry in 1994, was inducted into the Control magazine Process Automation Hall of Fame in 2001, was honored by InTech magazine in 2003 as one of the most influential innovators in automation, and received the ISA Life Achievement Award in 2010. Greg is the author of numerous books on process control, including Advances in Reactor Measurement and Control and Essentials of Modern Measurements and Final Elements in the Process Industry. Greg has been the monthly "Control Talk" columnist for Control magazine since 2002. Presently, Greg is a part time modeling and control consultant in Technology for Process Simulation for Emerson Automation Solutions specializing in the use of the virtual plant for exploring new opportunities. He spends most of his time writing, teaching and leading the ISA Mentor Program he founded in 2011.

 

Connect with Greg:

LinkedIn

 

Hunter Vegas, P.E., holds a B.S.E.E. degree from Tulane University and an M.B.A. from Wake Forest University. His job titles have included instrument engineer, production engineer, instrumentation group leader, principal automation engineer, and unit production manager. In 2001, he joined Avid Solutions, Inc., as an engineering manager and lead project engineer, where he works today. Hunter has executed nearly 2,000 instrumentation and control projects over his career, with budgets ranging from a few thousand to millions of dollars. He is proficient in field instrumentation sizing and selection, safety interlock design, electrical design, advanced control strategy, and numerous control system hardware and software platforms.

 

Connect with Hunter
LinkedIn

 

Greg McMillan
Greg McMillan
Greg McMillan has more than 50 years of experience in industrial process automation, with an emphasis on the synergy of dynamic modeling and process control. He retired as a Senior Fellow from Solutia and a senior principal software engineer from Emerson Process Systems and Solutions. He was also an adjunct professor in the Washington University Saint Louis Chemical Engineering department from 2001 to 2004. Greg is the author of numerous ISA books and columns on process control, and he has been the monthly Control Talk columnist for Control magazine since 2002. He is the leader of the monthly ISA “Ask the Automation Pros” Q&A posts that began as a series of Mentor Program Q&A posts in 2014. He started and guided the ISA Standards and Practices committee on ISA-TR5.9-2023, PID Algorithms and Performance Technical Report, and he wrote “Annex A - Valve Response and Control Loop Performance, Sources, Consequences, Fixes, and Specifications” in ISA-TR75.25.02-2000 (R2023), Control Valve Response Measurement from Step Inputs. Greg’s achievements include the ISA Kermit Fischer Environmental Award for pH control in 1991, appointment to ISA Fellow in 1991, the Control magazine Engineer of the Year Award for the Process Industry in 1994, induction into the Control magazine Process Automation Hall of Fame in 2001, selection as one of InTech magazine’s 50 Most Influential Innovators in 2003, several ISA Raymond D. Molloy awards for bestselling books of the year, the ISA Life Achievement Award in 2010, the ISA Mentoring Excellence award in 2020, and the ISA Standards Achievement Award in 2023. He has a BS in engineering physics from Kansas University and an MS in control theory from Missouri University of Science and Technology, both with emphasis on industrial processes.

Books:

Advances in Reactor Measurement and Control
Good Tuning: A Pocket Guide, Fourth Edition
New Directions in Bioprocess Modeling and Control: Maximizing Process Analytical Technology Benefits, Second Edition
Essentials of Modern Measurements and Final Elements in the Process Industry: A Guide to Design, Configuration, Installation, and Maintenance
101 Tips for a Successful Automation Career
Advanced pH Measurement and Control: Digital Twin Synergy and Advances in Technology, Fourth Edition
The Funnier Side of Retirement for Engineers and People of the Technical Persuasion
The Life and Times of an Automation Professional - An Illustrated Guide
Advanced Temperature Measurement and Control, Second Edition
Models Unleashed: Virtual Plant and Model Predictive Control Applications

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