The post Artificial Intelligence-Based Improved Classification of Two-Phase Flow Patterns [technical] first appeared on the ISA Interchange blog site.
This post is an excerpt from the journal ISA Transactions. All ISA Transactions articles are free to ISA members, or can be purchased from Elsevier Press.
Abstract: Flow pattern recognition is necessary to select design equations for finding operating details of the process and to perform computational simulations. Visual image processing can be used to automate the interpretation of patterns in two-phase flow. In this paper, an attempt has been made to improve the classification accuracy of the flow pattern of gas/ liquid two- phase flow using fuzzy logic and Support Vector Machine (SVM) with Principal Component Analysis (PCA). The videos of six different types of flow patterns namely, annular flow, bubble flow, churn flow, plug flow, slug flow and stratified flow are re- corded for a period and converted to 2D images for processing. The textural and shape features extracted using image processing are applied as inputs to various classification schemes namely fuzzy logic, SVM and SVM with PCA in order to identify the type of flow pattern. The results obtained are compared and it is observed that SVM with features reduced using PCA gives the better classification accuracy and computationally less intensive than other two existing schemes. This study results cover industrial application needs including oil and gas and any other gas-liquid two-phase flows.
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2006-2019 Elsevier Science Ltd. All rights reserved.
Source: ISA News
The post AutoQuiz: Cold Junction Compensation Is Required for Which Type of Temperature Measurement Device? first appeared on the ISA Interchange blog site.
This automation industry quiz question comes from the ISA Certified Control Systems Technician (CCST) program. Certified Control System Technicians calibrate, document, troubleshoot, and repair/replace instrumentation for systems that measure and control level, temperature, pressure, flow, and other process variables. Click this link for more information about the CCST program.
a) resistance temperature detector
b) thermocouple
c) infrared pyrometer
d) bi-metal thermometer
e) none of the above
Thermocouples generate millivolt signals, which can be correlated to the measured temperature. As with all voltage signals, the millivolt signal developed by the thermocouple must be referenced to a known voltage. For example, in current loops, we often use earth ground as a voltage reference (0V).
Any connection a thermocouple makes (including the connections of the thermocouple wires to a terminal block or PLC input card) will form an additional measuring junction. Therefore, a reference junction, called a cold junction, is used to provide a junction with a known, stable output. This allows the thermocouple to generate a millivolt signal along the wires that can be correlated directly to the temperature reading of the measured process.
The correct answer is B, thermocouple. A thermocouple is comprised of two wires of dissimilar metals, connected at one end, which is placed in the process to be measured. This is called the measuring junction.
The other three temperature measurement devices listed in the problem statement do not require a cold junction reference.
Reference: Goettsche, L.D. (Editor), Maintenance of Instruments and Systems, 2nd Edition
About the Editor
Joel Don is the community manager for ISA and is an independent content marketing, social media and public relations consultant. Prior to his work in marketing and PR, Joel served as an editor for regional newspapers and national magazines throughout the U.S. He earned a master’s degree from the Medill School at Northwestern University with a focus on science, engineering and biomedical marketing communications, and a bachelor of science degree from UC San Diego.
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Source: ISA News
The post How to Prevent Cavitation in Butterfly Control Valves first appeared on the ISA Interchange blog site.
Cavitation is the implosion of tiny vapor bubbles in a liquid when the static pressure reaches the vapor pressure of the specific liquid. This happens when, due to a high pressure differential across a valve, the resultant high velocity lowers the static pressure. Cavitation is a bane for the valve designer and valve user alike. It not only causes severe damage to valve trim, but also creates sound levels that can exceed 110 decibels.
The damage is caused when the imploding vapor bubbles create pressure waves that accelerate at values of 1.5 × 1011 m/s2 and reach velocities of 500 m/s. Even hardened steel cannot resist such an impact, even though the bubble size has a diameter of only about 200 micrometers.
There have been methods to eliminate, or at least reduce, cavitation in throttling valves. The simplest way is to reduce the pressure drop by changing the altitude of a valve or installing two valves in series. However, these approaches are usually not doable because of system restrictions. If possible, one should limit the valve’s pressure drop below the pressure level indicated by the cavitation index Xfz, where Xfz is the allowable delta P divided by inlet pressure minus vapor pressure (pressures in absolute terms). Xfz values may be gleaned from figure 7.
Cv is an industrywide flow coefficient defined as Cv = 1.17 × [ Q / (P1 – P2)0.5], where Q = m3/hr of cold water and P is in bar(abs) = (1 × 105 Pascal). For example, a DN 100 conventional globe valve with a required Cv of 50 has an Xfz factor of 0.34.
Other known ways of fighting cavitation is injecting air into the fluid or using the vacuum pressure created by the cavitating fluid. Figure 1 shows how this can be done. A butterfly valve has a hollow stem conducting outside air into a number of small holes and dispersing the air into the water. This can only be done if the vapor pressure is in a vacuum and if the particular fluid tolerates air inclusion.
Figure 1. A butterfly valve reduces cavitation by utilizing air sucked in by the liquid vapor through a series of holes. A check valve prevents the escape of liquid in case there is no vacuum downstream of the vane.
Another quite effective way of reducing cavitation is by utilizing drilled cages inside globe valves, sometimes using several hundred drilled holes. The effect is twofold. First, the small holes increase the Xfz factor, and second, the resulting small jets create only localized cavitation. The drawback is that this is an expensive solution and cannot readily be scaled up.
Quite often, butterfly valves are used especially in larger sizes due to lower cost. To reduce the tendency to cavitate in such valves, companies employ proprietary vane designs. Figure 2 shows such a design, using a row of teeth on both leading edges of the vane to split up the liquid jets.
Anecdotal information indicates that this design indeed reduces cavitation, as these valves were used successfully in Japan, in sizes up to 2 meters for drinking water pipelines. These valves had the drawbacks that they cannot provide tight shutoff and cannot offer the more popular equal percentage flow characteristic.
Another design solves such deficiencies (figure 3). Here, a low-noise insert is attached to a conventional triple eccentric butterfly valve, which provides shutoff. The attachment not only reduces cavitation (as explained later), but also creates an equal percentage flow characteristic due to the special configuration of the teeth part of the attachment.
Figure 2. A low noise and activation butterfly valve using opposed rows of teeth splitting up the fluid stream, changing frequency, and increasing the Xfz factor. Source: Tomoe Company
Figure 3. A Sharktooth butterfly system using conventional shutoff butterfly valves. By attaching a multitooth element, it has higher fluid resistant and Xfz factors. The teeth profiles provide an equal percentage flow characteristic. Source: Yeary Associates, Inc.
First a little theory: Most of us are by now familiar with the fluid resistant (FL) factor, denoting pressure recovery in a valve. This factor has been an invaluable aid in proper valve sizing, even though the concept of pressure recovery in valves has only been known since 1963.
What most people may not know is that the FL factor tells us how much of the kinetic energy (velocity head) in a valve is converted into turbulence and heat. There is a correlation between FL and the head loss coefficient K or Σ; here K = FL2. Incidentally, FL works for all Newtonian fluids, whether liquids or gases.
Assume a valve has an FL of 1. Here all kinetic energy is converted into heat (turbulence), and therefore, the valve cannot experience cavitation. On the other hand, consider a conventional butterfly valve with a typical FL of 0.65. Here the K factor is 0.422, meaning only 42 percent of the kinetic energy is converted, and the rest is used to evaporate some of the liquid; the vapors then implode in the pressure recovery zone of the valve to cause damage and noise.
Figure 4 shows a pressure diagram using 10 bar absolute as inlet pressure and 4.5 bar as outlet pressure. Using the typical butterfly valve FL of 0.65, we notice a velocity head of 13 bar. This is a theoretical number, since the velocity head cannot exceed the vapor pressure. But what it means is that an energy equivalent of 2 bar is used to evaporate the liquid, and cavitation will occur. On the other hand, if another valve with an FL of 0.84 were used, the velocity head will only be 7.8 bar, and the bottom will stay well above the vapor pressure, hence, no cavitation.
Figure 4. Graphic presentation of pressure gradients inside a valve at 5.5 bar pressure drop
Having realized the importance of head loss, it was found that the configuration of the Yeary valve indeed produced sufficient hydraulic friction to yield high FL numbers. The graph in figure 5 shows the results of a water test on a DN 150 (6-inch) valve at 60 degrees open (a large opening for a valve having high pressure drops) and an FL factor of 0.8. Here the inlet pressure was 7.7 bar absolute with pressure drops down to just below 1 bar absolute.
It is perhaps astonishing how closely the calculated levels correspond with the microphone readings. Note that the blue line corresponds to the 30 log(10X) relationship predicted for turbulent water. Cavitation occurs at 5 bar pressure drop (64 percent of the inlet pressure). The cavitation amplitude was calculated as 5.6 dB, which matches the test data. Note that the increase in slope terminates when X is equal to FL2, which happens around a P2 of 3 bar absolute.
To purchase a copy of Fluid Mechanics of Control Valves: How Valves Control Your Process, click this link. To download a free, 42-page excerpt from the book, click this link.
This test shows that calculated turbulent water slopes can easily be used to predict the onset of cavitation. In this case it happened around an outlet pressure of 3 bar, as is predicted by the equation: P2cav. = P1 – [(P1 – Pv) × FL2], which calculates the limit to be 2.8 bar. The estimated cavitation sound level closely matches the test data despite a lack of test points. As shown in the graph, when the outlet pressure dips into vacuum, water saturates with vapor, and there is a sudden drop in sound.
These tests have been duplicated at 20 and 30 degrees opening, yielding almost identical results. At 20 degrees open, for example, the 0.150 valve only started cavitating at an Xfz of 0.83 with a cavitation amplitude of only 3 dB.
Figure 5. Results of a water test on a DN 150 (6”) valve at 60 degrees open and an FL factor of 0.8
As shown in figure 6 (below), the cavitation only happens at a high pressure drop of 6.3 bar (X = 0.81). The cavitation amplitude of 3 dB matches the prediction, where amplitude = 60 log (Xy / Xfz), Xfz = 0.81, and Xy = 0.91. The apparent discrepancy of 4 dB and 5 dB between test data and calculations can partially be explained by significant pump noise in the laboratory.
All tests confirm the exceptional high conversion rate of dynamic fluidic energy to static energy, thus avoiding cavitation in all but the very high pressure drop regions. As the designer of the valve, I can attest to the veracity of these features. These tests also show that sound can play an important role in testing valves for cavitation characteristics.
A globe valve is a two-stage device consisting of a plug and seat ring having an FL of perhaps 0.6, implying an Xfz factor of 0.36. The valve body, having a tortuous flow path, may have an FL of 0.9, making the overall FL = 0.82. Here the governing Xfz is that of the valve trim (where cavitation actually occurs), and the relationship Xfz = square root of overall FL does not apply.
All tests were performed at the Utah State Water Research Laboratory in Logan, Utah, under the guidance of Professor Michael Johnson, PhD, PE. I thank Dr. Johnson for his help and valuable advice.
Figure 6. Data from tests conducted with a 10-inch Sharktooth valve to verify that the beneficial effects can be scaled up
Figure 7. Xfz values. Note that the graph shows both the European (in meters) and the U.S. (in inches) systems on the x-axis.
Graph references: IEC 60534-8-4: Prediction of noise generated by hydrodynamic flow and “A fresh look: How to estimate cavitation noise” Valve World, by H.D. Baumann
About the Author
Hans D. Baumann, is a world-renowned expert on control valves. He is credited with more than 100 U.S. patents relating to valve control technology and has written eight books (among them the Control Valve Primer: A User’s Guide) on the subject. He is: an Honorary Member of ISA, ASME, the Fluid Controls Institute, and the Spanish Chemical Engineering Society; a member of Sigma Xi; and an inductee of the Automation Control Hall of Fame. For many years, he represented the US at the IEC International Standards Committee on control valves. In 1977, he founded H. D. Baumann Assoc., Ltd., a manufacturer of control valves. The company was initially acquired by Fisher Instruments, and is now part of Emerson Process Management. During his career, Hans has served in numerous positions, including chief engineer at W. & T. Co., a German valve supplier; manager of research & development at Worthington S/A in France; director of engineering at Cashco; vice president at Masoneilan International, Inc.; and senior vice president of technology at Fisher Controls. Hans holds degrees from Case institute of Technology (now part of Case Western Reserve University) and Northeastern University, and earned a doctorate degree in mechanical engineering from Columbia Pacific University.
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A version of this article also was published at InTech magazine.
Source: ISA News
The post Four Quick Tips for Making Smart, Strategic Decisions at Your Industrial Plant or Facility first appeared on the ISA Interchange blog site.
During an automation leadership conference at ISA headquarters, Peter Martin, PhD, vice president of business value consulting at Schneider Electric (and a real hero of U.S. manufacturing, as named by Fortune magazine) delivered a presentation titled The Future of Automation and Control that enchanted the audience. He described three driving forces that he predicts will shape the future of automation:
Martin explained how these forces, along with other workforce shifts (e.g., the ageing workforce and the lack of skilled workers available to replace them), will influence various aspects of automation and control, which really hit home.
I bring this up, because as I sat there listening, I realized that these forces are happening throughout all of manufacturing (whether we like it or not). These trends will affect us all personally at some point—and they should affect the decisions we make and how we make them. The ability to make better decisions will not only help you personally in your career, but also help your company progress.
Before diving into the tips, know that successful decision making is a bit of an art that is influenced by many factors, including your plant environment, marketplace, company objectives, company culture, and available resources. So, when considering these four quick tips, use them as a guideline to steer your decision-making process.
With the increasing speed of business and high workload, it may be easier to decide, for example, to simply replace an existing automation system with the same exact version of a new one, because it is quicker and easier. Do not fall into this trap. Ask yourself if this is a wise decision that will not only be beneficial in the short term, but add value now and for years to come. Consider the new technology available, and analyze any accessible data from your existing system, both historical and current. Use the information you have available. Take the initiative to research new technology to improve the process. Considering future needs and improving a process is both a smart and strategic decision.
Set clear goals and reasons before you make a decision, to ensure the choices you make align with the end objective or goal. Going back to Martin’s driving force of measureable business value, ask yourself: what are the measureable results that you can report as a result of this decision? What are your key performance indicators? More and more companies require a concrete return on investment or cost-avoidance analysis for an automation system investment. Measureable business value will be a vital necessity in the years ahead.
If you want to invest in a continuing education course and need management’s approval, be prepared to justify the investment (measureable business value again). Be sure you are able to communicate the value it will bring for both you and the company. Get feedback from stakeholders in the decision-making process, and those who will be affected by the knowledge you gain. When prepared, if possible, ask the person who has the authority to make the final approval, so you can handle objections directly, should they arise.
You make all types of decisions every day for yourself and your company and that will never end. Smart, strategic decisions involve a more thoughtful process focused on the long term. You can learn something from the decisions you make and apply those lessons the next time an opportunity to make a smarter decision arises. The bottom line is do not forget to take the time to reflect and analyze the results.
Making smart, strategic decisions is linked to the ability to define the needs of the business or application, your goals, and the purpose, and finally to execute based on those criteria. Training yourself and your staff to do so is vital to successful workforce development.
About the Author
Katie Turner, marketing manager, has more than 10 years of experience developing and executing integrated marketing strategies. At Beamex, she oversees marketing operations for North American.
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A version of this article also was published at InTech magazine.
Source: ISA News
The post AutoQuiz: What Security Property Is Affected If a Hacker Intercepts and Changes Set Point Data? first appeared on the ISA Interchange blog site.
This automation industry quiz question comes from the ISA Certified Automation Professional (CAP) certification program. ISA CAP certification provides a non-biased, third-party, objective assessment and confirmation of an automation professional’s skills. The CAP exam is focused on direction, definition, design, development/application, deployment, documentation, and support of systems, software, and equipment used in control systems, manufacturing information systems, systems integration, and operational consulting. Click this link for more information about the CAP program.
a) integrity
b) functionality
c) availability
d) defensibility
e) none of the above
Answer B is incorrect, because functionality is not a basic security property.
Answer C is incorrect, because the problem statement did not address the availability of data. It appears that only the value of the set point (data integrity) was affected.
Answer D is incorrect, because defensibility is not a basic security property, but rather a measure of the vulnerability of a system.
The correct answer is A, integrity. Data integrity implies that the data received is the same (value, format, quality) as the data sent. If a hacker is successful in changing set point data as that data travels over the network, the hacker has compromised integrity of the data, since it is no longer the same when received as when sent.
Reference: Nicholas Sands, P.E., CAP and Ian Verhappen, P.Eng., CAP., A Guide to the Automation Body of Knowledge. To read a brief Q&A with the authors, plus download a free 116-page excerpt from the book, click this link.
About the Editor
Joel Don is the community manager for ISA and is an independent content marketing, social media and public relations consultant. Prior to his work in marketing and PR, Joel served as an editor for regional newspapers and national magazines throughout the U.S. He earned a master’s degree from the Medill School at Northwestern University with a focus on science, engineering and biomedical marketing communications, and a bachelor of science degree from UC San Diego.
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Source: ISA News
The post New Method for Tuning PID Controllers Using a Symmetric Send-On-Delta Sampling Strategy [technical] first appeared on the ISA Interchange blog site.
This post is an excerpt from the journal ISA Transactions. All ISA Transactions articles are free to ISA members, or can be purchased from Elsevier Press.
Abstract: In this paper we present a new method for tuning PI controllers with symmetric send-on-delta (SSOD) sampling strategy. First we analyze the conditions that produce oscillations in event based systems considering SSOD sampling strategy. The Describing Function is the tool used to address the problem. Once the conditions for oscillations are established, a new robustness to oscillation performance measure is introduced which entails with the concept of phase margin, one of the most traditional measures of relative stability in closed-loop control systems. Therefore, the application of the proposed robustness measure is easy and intuitive. The method is tested by both simulations and experiments. Additionally, a Java application has been developed to aid in the design according to the results presented in the paper.
Free Bonus! To read the full version of this ISA Transactions article, click here.
Enjoy this technical resource article? Join ISA and get free access to all ISA Transactions articles as well as a wealth of other technical content, plus professional networking and discounts on technical training, books, conferences, and professional certification.
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2006-2019 Elsevier Science Ltd. All rights reserved.
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The post How to Implement Effective Safety Instrumented Systems for Process Automation Applications first appeared on the ISA Interchange blog site.
In the ISA Mentor Program, I am providing guidance for extremely talented individuals from countries such as Argentina, Brazil, Malaysia, Mexico, Saudi Arabia, and the USA. This question comes from Hariharan Ramachandran.
Hariharan starts an enlightening conversation introducing platform independent key concepts for an effective safety instrumented system with the Mentor Program resource Len Laskowski, a principal technical SIS consultant, and Hunter Vegas, co-founder of the Mentor Program.
Hariharan Ramachandran, a recent resource added to the ISA Mentor Program, is a control and safety systems professional with various levels of experience in the field of Industrial control, safety and automation. He has worked for various companies and executed global projects for oil and gas and petrochemical industries gaining experience in the entire life cycle of industrial automation and safety projects.
Len Laskowski is a principal technical SIS consultant for Emerson Automation Solutions, and is a voting member of ISA84, Instrumented Systems to Achieve Functional Safety in the Process Industries.
Hunter Vegas, P.E., has worked as an instrument engineer, production engineer, instrumentation group leader, principal automation engineer, and unit production manager. In 2001, he entered the systems integration industry and is currently working for Wunderlich-Malec as an engineering project manager in Kernersville, N.C. Hunter has executed thousands of 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. Hunter earned a B.S.E.E. degree from Tulane University and an M.B.A. from Wake Forest University.
How is the safety integrity level (SIL) of a critical safety system maintained throughout the lifecycle?
The answer might sound a bit trite by the simple answer is by diligently following the lifecycle steps from beginning to end. Perform the design correctly and verify that it has been executed correctly. The SIS team should not blindly accept HAZOP and LOPA results at face value. The design that the LOPAs drive is no better than the team that determined the LOPA and the information they were provided. Often the LOPA results are based on incomplete or possibly misleading information. I believe a good SIS design team should question the LOPA and seek to validate its assumptions. I have seen LOPA’s declare that there is no hazard because XYZ equipment protects against it. But a walk in the field later discovered that equipment was taken out of service a year ago and had not yet been replaced. Obviously getting the LOPA/Hazop right is the first step.
The second step is to make sure one does a robust design and specifies good quality instruments that are a good fit for the application. For example, a vortex meter may be a great meter for some applications but a poor choice for others. Similarly certain valve designs may have limited value as a safety shutdown valve. Inexperienced engineers may specify Class VI shutoff for on-off valves thinking they are making the system safer, but Class V metal seat valves would stand up to the service much better in the long run since the soft elastomer seats can easily be destroyed in less than month of operation. The third leg of this triangle is using the equipment by exercising it and routinely testing the loop. Partial stroke testing the valves is a very good idea to keep valves from sticking. Also for new units that do not have extensive experience with a process, the SIF components (valves and sensors) should be inspected at the first shutdown to assess their condition. This needs to be done until a history with the installation can be established. Diagnostics also fall into this category, deviation alarms, stroke time and any other diagnostics that can help determine the SIS health is important.
The safety instrumented function has to be monitored and managed throughout its lifecycle. Each layer in a safety protection system must have the ability to be audited. SIS verification and validation process provides a high level of assurance that the SIS will operate in accordance with its safety requirements specification (SRS). The proof testing must be carried out periodically at the intervals specified in the safety requirement specification. There should be a mechanism for recording of SIF life event data (proof test results, failures, and demands) for comparison of actual to expected performance. Continuous evaluation and improvement is the key concept here in maintaining the SIS efficiently.
What is the best approach to eliminate the common cause failures in a safety critical system?
There are many ways that common cause failures can creep into a safety system design. Some of the more common ways include:
Both, random and systematic events can induce common cause failure (CCF) in the form of single points of failure or the failure of redundant devices.
Random hardware failures are addressed by Design architecture, diagnostics, estimation (analysis) of probabilistic failures, design techniques and measures (to IEC 61508‐7).
Systematic failures are best addressed through the implementation of a protective management system, which overlays a quality management system with a project development process. A rigorous system is required to decrease systematic errors and enhance safe and reliable operation. Each verification, functional assessment, audit, and validation is aimed at reducing the probability of systematic error to a sufficiently low level.
The management system should define work processes, which seek to identify and correct human error. Internal guidelines and procedures should be developed to support the day-to-day work processes for project engineering and on-going plant operation and maintenance. Procedures also serve as a training tool and ensure consistent execution of required activities. As errors or failures are detected, their occurrence should be investigated, so that lessons can be learned and communicated to potentially affected personnel.
An incident happened at a process plant, what are all the engineering aspects that needs to be verified during the Investigation?
I would start at the beginning of the lifecycle look at Hazop and LOPA’s to see that they are done properly. Look to see that documentation is correct; P&IDs, SRS, C&Es, MOC and test logs and procedures. Look to see where the break down occurred. Were things specified correctly? Were the designs verified? Was the System correctly validated? Was proper training given? Look for test records once the system was commissioned.
Usually the first step is to determine exactly what happened separating conjecture from facts. Gather alarm logs, historian data, etc. while it is available. Individually interview any personnel involved as soon as possible to lock in the details. With that information in hand, begin to work backwards determining exactly what initiated the event and what subsequent failures occurred to allow it to happen. In most cases there will be a cascade of failures that actually enabled the event to happen. Then examine each failure to understand what happened and how it can be avoided in the future. Often there will be a number of changes implemented. If the SIS system failed, then Len’s answer provides a good list of items to check.
Also verify if the device/equipment is appropriately used within the design intent.
What are all the critical factors involved in decommissioning a control systems?
The most critical factor is good documentation. You need to know what is going to happen to your unit and other units in the plant once an instrument, valve, loop or interlock is decommissioned. A proper risk and impact assessment has to be carried out prior to the decommissioning. One must ask very early on in a project’s development if all units controlled by the system are planning to shut down at the same time. This is needed for maintenance and upgrades. Power distribution and other utilities are critical. One may not be able to demo a system because it would affect other units. In many cases, a system cannot be totally decommissioned until the next shutdown of the operating unit and it may require simultaneous shutdowns of neighboring units as well. Waste management strategy, regulatory framework and environmental safety control are the other factors to be considered.
A proper risk and impact assessment has to be carried out prior to the decommissioning. Waste management strategy, regulatory framework and environmental safety control are the other factors to be considered.
The ISA Mentor Program enables young professionals to access the wisdom and expertise of seasoned ISA members, and offers veteran ISA professionals the chance to share their wisdom and make a difference in someone’s career. Click this link to learn more about the ISA Mentor Program.
See the ISA book 101 Tips for a Successful Automation Career that grew out of this Mentor Program to gain concise and practical advice. See the InTech magazine feature article Enabling new automation engineers for candid comments from some of the original program participants. See the Control Talk column How to effectively get engineering knowledge with the ISA Mentor Program protégée Keneisha Williams on the challenges faced by young engineers today, and the column How to succeed at career and project migration with protégé Bill Thomas on how to make the most out of yourself and your project. Providing discussion and answers besides Greg McMillan and co-founder of the program Hunter Vegas (project engineering manager at Wunderlich-Malec) are resources Mark Darby (principal consultant at CMiD Solutions), Brian Hrankowsky (consultant engineer at a major pharmaceutical company), Michel Ruel (executive director, engineering practice at BBA Inc.), Leah Ruder (director of global project engineering at the Midwest Engineering Center of Emerson Automation Solutions), Nick Sands (ISA Fellow and Manufacturing Technology Fellow at DuPont), Bart Propst (process control leader for the Ascend Performance Materials Chocolate Bayou plant), Angela Valdes (automation manager of the Toronto office for SNC-Lavalin), and Daniel Warren (senior instrumentation/electrical specialist at D.M.W. Instrumentation Consulting Services, Ltd.).
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.
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Source: ISA News
The post AutoQuiz: What Is a Schematic Representation of a Complete Hydraulic, Electric, Magnetic, or Pneumatic Circuit Called? first appeared on the ISA Interchange blog site.
This automation industry quiz question comes from the ISA Certified Control Systems Technician (CCST) program. Certified Control System Technicians calibrate, document, troubleshoot, and repair/replace instrumentation for systems that measure and control level, temperature, pressure, flow, and other process variables. Click this link for more information about the CCST program.
a) process and instrumentation diagram (P&ID)
b) logic diagram
c) loop diagram
d) process flow diagram
e) all of the above
Answer A, P&ID, is a diagram that shows the interconnection of process equipment and the instrumentation used to control the process.
Answer B, logic diagram, is a diagram used to define on/off control.
Answer D, process flow diagram, is a diagram that defines a process schematically and shows how much of each product a plant might make.
The correct answer is C, loop diagram. This diagram shows complete details of a hydraulic, electric, magnetic, or pneumatic circuit, showing all of the interconnections, components, and devices that participate in that circuit.
Reference: Goettsche, L.D. (Editor), Maintenance of Instruments and Systems, 2nd Edition
About the Editor
Joel Don is the community manager for ISA and is an independent content marketing, social media and public relations consultant. Prior to his work in marketing and PR, Joel served as an editor for regional newspapers and national magazines throughout the U.S. He earned a master’s degree from the Medill School at Northwestern University with a focus on science, engineering and biomedical marketing communications, and a bachelor of science degree from UC San Diego.
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The post What Is the Connection Between All of the Inputs and the Output of an Industrial Process? first appeared on the ISA Interchange blog site.
While I was completing my bachelor’s degree in electrical engineering, I was, among other things, studying “automatic process control.” I was using a couple of texts that elucidated terms and concepts such as “observability,” “transfer function”, and “sensitivity.” I recall a huge hit by The Rolling Stones and I’m struck with its pertinence to relating process observations with process control.
In many situations it’s hard to get every observation you need when, where, and how you need it. Often, some assessment of importance is useful in deciding what, how, and where to measure something. Mick Jagger provided the insight:
“You can’t always get what you want, but if you try sometimes, you might find, you get what you need.”
There are things you need to know in an application and there are things you can measure. The characteristics of a measurement include how it was measured, where it was measured, and when it was measured. What you are trying to assess is how well the outcome of the underlying process meets expectations. If the results are disappointing, we wonder about and investigate why. This can be a tedious process, especially with new ideas based on weak or untested science (or creative conjecture). Around a third of the way through his book Automatic Control Systems, Dr. Benjamin Kuo introduces the idea of sensitivity and use of the “sensitivity function” to assess it.
Sensitivity addresses the question, “How does this parameter I’m investigating affect the intended outcome?” This helps answer some profound questions, including:
This thinking can be applied to all processes. A good friend was recently wondering how his pension for a lifetime of municipal work could dissolve into a tableful of new job applications, suddenly necessary for his future.
Clearly, the “output” from that system, his pension, could be assessed as “non-conforming to expectations” and “inadequate.” The “inputs,” the payroll deductions, work concessions, etc. over the years, were certainly observable. The “process” depended on investment practices, economic factors, and assumptions; not just hopes and expectations. In his case, lifelong plans changed. In the case of a process automation engineer optimizing a control system, similar manifestations of the same root concepts can profoundly affect his company’s future as well as his own.
A transfer function describes the connection between the inputs and related factors with the outcome we desire. Fundamentally, an equation is written in which the outcome is set equal to the mathematical collection of process observations that science says will produce or influence it. The transfer function describes in explicit or characteristic terms how the inputs become the output. Just because it’s easy and familiar, let’s consider the pressure lost in moving a fluid in a full pipe from one place to another. The most common methodology is the Darcy equation which, for this simple example, can be written as:
where:
Essentially, the sensitivity function relates a change in the output, in this case, to the change in one of the parameters on which it depends. This relationship could be explored several ways but the fast way through the concepts is to observe that the sensitivity of to velocity (for example) can be found by taking the partial derivative of with respect to v. The operator symbol ¶ is usually used to denote partial differentiation. In this case the result is:
From this we deduce that how sensitive ΔP is to velocity depends linearly on the velocity – changes at higher velocity produce more effect than changes at lower velocity. Thinking about it, that seems “normal” considering v is “squared” in the transfer function, accentuating its effect as velocity becomes larger and becoming less and less significant as it become small. Remember, we are investigating the sensitivity of the change in pressure drop to the change in velocity, not the value of the pressure decrease resulting from a particular velocity. This calculation can be repeated for each parameter of interest in the equation.
Having assessed the importance of v we can move onto assessing the methodology, placement and timing of the measurements available to the system for use in appropriate process observation and effective control. If sensitivity to a parameter is low or non-existent the care involved with observing it is less important. If the sensitivity is very high then obtaining an appropriate, accurate, and timely observation can be crucial.
What about the sensitivity to the friction factor,ƒ? That seems simple to evaluate until we realize that the calculation of it depends on several other process parameters, such as the viscosity of the fluid, which depends on its temperature. In some cases, it might depend on the pressure, or pipe condition, or even the exact composition of the actual fluid – there are equations pertaining to friction factor for specific fluids over a variety of conditions. Including all that complicates the transfer function but improves the visibility of the issues involved. In some cases, a broadly applicable and accurate transfer function can be very hard to develop or to solve in a manner consistent with actual process behavior. Sometimes the cost of knowing these things can exceed their value. Conversely, sometimes the value is realizing what things are important and how they are changing.
Sometimes sensitivity takes us past the limits of what we can reliably or economically observe. Exploring it, though, discloses a lot about reasonable expectations and divergences from them. Future discussions about some observability issues will come back to this idea of sensitivity.
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About the Author
Edward Farmer has more than 40 years of experience in the “high tech” part of the oil industry. He originally graduated with a bachelor of science degree in electrical engineering from California State University, Chico, where he also completed the master’s program in physical science. Over the years, Edward has designed SCADA hardware and software, practiced and written extensively about process control technology, and has worked extensively in pipeline leak detection. He is the inventor of the Pressure Point Analysis® leak detection system as well as the Locator® high-accuracy, low-bandwidth leak location system. He is a Registered Professional Engineer in five states and has worked on a broad scope of projects worldwide. His work has produced three books, numerous articles, and four patents. Edward has also worked extensively in military communications where he has authored many papers for military publications and participated in the development and evaluation of two radio antennas currently in U.S. inventory. He is a graduate of the U.S. Marine Corps Command and Staff College. He is the owner and president of EFA Technologies, Inc., manufacturer of the LeakNet family of pipeline leak detection products.
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ISA standards offer a wealth of knowledge and guidance to provide safer and more reliable and effective automation systems. In this interactive presentation, Nick Sands provides an extensive overview of ISA standards and considerable insight into the opportunities for using and being involved in developing ISA standards.
Want to learn more about ISA standards? Click this link to visit the main ISA Standards website page.
About the Featured Presenter
Nicholas P. Sands, P.E., CAP, serves as senior manufacturing technology fellow at DuPont, where he applies his expertise in automation and process control for the DuPont Safety and Construction business (Kevlar, Nomex, and Tyvek). During his career at DuPont, Sands has worked on or led the development of several corporate standards and best practices in the areas of automation competency, safety instrumented systems, alarm management, and process safety. Nick is: an ISA Fellow; co-chair of the ISA18 committee on alarm management; a director of the ISA101 committee on human machine interface; a director of the ISA84 committee on safety instrumented systems; and secretary of the IEC (International Electrotechnical Commission) committee that published the alarm management standard IEC62682. He is a former ISA Vice President of Standards and Practices and former ISA Vice President of Professional Development, and was a significant contributor to the development of ISA’s Certified Automation Professional program. He has written more than 40 articles and papers on alarm management, safety instrumented systems, and professional development, and is co-author of the new edition of A Guide to the Automation Body of Knowledge. Nick is a licensed engineer in the state of Delaware. He earned a bachelor of science degree in chemical engineering at Virginia Tech.
The ISA Mentor Program enables young professionals to access the wisdom and expertise of seasoned ISA members, and offers veteran ISA professionals the chance to share their wisdom and make a difference in someone’s career. Click this link to learn more about the ISA Mentor Program.
About the Presenter
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.
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