Such a modification of the valve’s inherent characteristic is similar to placing a mechanical cam in the travel feedback linkage of a pneumatic positioner. This can convert, say, a butterfly valve from linear to equal percentage. The trouble is that the travel vs. flow coefficient (Cv) of a butterfly valve remains linear.
The result is that the signal resolution at low flow becomes very poor because, with an equal percentage output signal at low flows, the valve travel is very small compared to a given signal change. Therefore, in such cases the valve’s dead band becomes high compared to its signal resolution.
Valves Can Also Measure the Flow
A control valve is a variable area flow meter with a variable pressure drop. Just as the float position in a rotameter (a constant ΔP flowmeter) can indicate the flow, the stem position of a control valve can do the same if the ΔP can be detected. Naturally, in order to do this, accurate knowledge of the valve characteristics and the process properties of the flowing fluid must be provided.
Smart valves can measure the flow through the valve by solving the appropriate valve sizing equation for flow. For example, for turbulent, non-choked liquids, flow (q) can be obtained from a formula (click the Download Now button below for a .pdf version of this formula) if the valve capacity coefficient (Cv), the piping geometry coefficient (Fp), the liquid specific gravity (Gf) and pressure difference (ΔP) across the valve are known. (For equations to calculate the piping coefficients or for equations to be used when the process fluid is a gas or a choked liquid, refer to the 2nd Volume of the Instrument Engineer’s Handbook.
For smart valves of the future to accurately measure their own flow, they must be provided with sufficient intelligence to identify the sizing equation that is applicable. Therefore, they will have to be able to detect laminar flow condition in viscous, choking conditions in cavitating liquid or sonic flow in gas flow applications. Naturally, the other requirement is to be able to accurately measure the variables that are required for solving the applicable equations. The required measurements include valve stem position, inlet, outlet and vena contracta pressures, flowing temperature, etc.
Yet, the potential advantages of such smart valves much outweigh the required investment of time and money. The savings include the elimination of both the initial cost of purchasing and installing, and the energy cost of operating, a separate flow sensor. An added advantage can be the increased rangeability of the flow measurement obtained from the valve. This is because the rangeability of traditional flow detectors is usually 3:1 to 10:1, while control valves can provide rangeabilities of 25:1 to over 100:1 because of their variable area orifices.
Self Diagnostics and Control
If the sensors of the intelligent control valve are connected to a PID chip within the valve positioner, the smart valve becomes a complete local control loop. In that case, the operator’s displays need to be provided in a location from which the operator can conveniently reconfigure the control loop or recalibrate the valve as well as to adjust the limits of its travel.
Smart valves can provide improved maintenance through self-diagnostics. If the proper intelligence is provided, the valve can compare its own behavior with its past performance. When the same conditions result in different valve openings, it can conclude, for example, that packing lubrication is needed or that the valve is getting plugged. When the conclusion of the diagnosis is that the stem is sticking, or that the trim is worn (or any other changes that might warrant maintenance), the intelligent valve can automatically request and schedule its own maintenance.
1. Baumann,Hans D., “Intelligent Valves, Positioners, Accessories,” Instrument Engineers’ Handbook, Volume 2, 4th edition, CRC Press, 2005.
2. Schneider, Hans-Josef, “Digital Feldgeraete: Vorteile, Probleme und Anforderungen aus Anwendersicht,” Praxis, atp Automatisierungstechnische Praxis, April (1995), pp. 50-54.
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Click the Download Now button below for a .pdf version of the formula referred to in this article.