How do you analyze and interpret the data from your control valve endurance test?
Control valves are essential devices for regulating fluid flow in various industrial processes. However, they are also subject to wear and tear, which can affect their performance and reliability over time. Therefore, it is important to conduct regular endurance tests on your control valves to assess their condition and identify any potential issues. In this article, you will learn how to analyze and interpret the data from your control valve endurance test and what to look for in terms of key indicators and trends.
Before beginning an endurance test on a control valve, it is essential to ensure that the test setup and procedure are suitable for the type and application. Following relevant standards and guidelines, such as ANSI/ISA-75.13 or IEC 60534-4, is essential as they specify the test parameters, methods, and criteria for control valve endurance testing. Generally, it is necessary to measure and record data such as valve stroke and position, input and output signals, actuator force or torque, flow rate and pressure drop, leakage rate and noise level, temperature and vibration during the test. Additionally, performing a baseline test before and after the endurance test is necessary to compare the valve performance and detect any changes or deviations.
Analyzing and interpreting data collected from an endurance test can help to evaluate the condition and performance of a control valve. To do this, you can use various tools and techniques, such as graphs, charts, tables, statistics, and software. During data analysis and interpretation, you should look for aspects such as valve hysteresis and repeatability, dead band and resolution, and rangeability and linearity. For example, hysteresis and repeatability can be calculated by plotting the valve stroke versus the input signal to find the maximum deviation between the opening and closing curves. Similarly, dead band and resolution can be determined by applying small increments or decrements of the input signal to observe the corresponding changes in the valve stroke. Finally, rangeability and linearity can be found by plotting the valve flow rate versus the valve stroke or the valve pressure drop versus the valve stroke to calculate the ratio or deviation from a straight line.
It is important to not only look at individual data points, but to also examine the data trends and patterns over time in order to identify any gradual or sudden changes in your control valve performance and condition. You should search for signs of deterioration or damage in the valve components, such as the valve seat, plug, stem, packing, actuator, or diaphragm. This can be done by monitoring the increase or decrease in the valve leakage rate, noise level, temperature, or vibration over time. Additionally, you should look for signs of normal wear and tear in these components by monitoring the change in the valve hysteresis, repeatability, dead band, resolution, rangeability, or linearity over time. If a high leakage rate, noise level, temperature, or vibration is detected it could indicate a severe valve degradation or failure and may require repair or replacement. If there is a slight change in these parameters it could indicate a moderate valve wear and tear and may require adjustment or maintenance.
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Tony M Poole
AOV Senior Tester at Duke Energy Corporation (Retired)
In my experience packing load is a big factor in good control valve performance. Too high packing load causes stick, slip, overshoot problems. Too low packing load can also cause overshoot problems. Modern valve packing provides good leakage protection at lower torque loads. Most packing manufacturers have data on optimal packing load. Once established, that optimal packing load should be applied every time the vakve is tested.
After analyzing and interpreting your data, you need to compare and evaluate them against the baseline test results and acceptance criteria to determine your control valve performance and condition. You should compare the data from the before and after baseline tests to see if there are any significant differences or deviations in valve performance parameters, such as hysteresis, repeatability, dead band, resolution, rangeability, or linearity. A large difference or deviation indicates a poor valve performance or a faulty valve component. Additionally, you should compare the data from the endurance test to the acceptance criteria specified by standards, guidelines, or manufacturers to see if they meet or exceed the minimum or maximum values or limits for valve performance parameters. Lastly, evaluate the overall data from the endurance test to see if they show any consistent or inconsistent trends or patterns for valve performance parameters. A consistent trend or pattern indicates a stable valve performance or a predictable valve behavior, while an inconsistent trend or pattern indicates an unstable valve performance or an unpredictable valve behavior.
The final step of your data analysis and interpretation is to report and document your findings and recommendations for your control valve endurance test. To present your data in a logical and organized manner, use clear and concise language as well as tables, graphs, charts, diagrams, or images to illustrate your data and emphasize the key points or results. Additionally, include all the information and details about your test setup, procedure, parameters, methods, criteria, data, analysis, interpretation, comparison, evaluation, findings, and recommendations. To provide extra information or sources you can use appendices, references or footnotes. Lastly, adhere to the applicable standards, guidelines or protocols for data reporting and documentation in your industry or sector. You can also use templates, formats or styles that are consistent with your organization or project requirements.
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