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Valve analysis software plug-in

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article image Providing key information to maximise equipment performance.

FLOWSERVE has introduced Flowserve ValveAnalysis, a software plug-in for Emerson Process Management's AMS suite of asset management tools.

Flowserve ValveAnalysis enables AMS users to run diagnostic signatures for Flowserve valves, actuators and positioners, providing key information that can be used to maximise equipment performance.

Adding informative diagnostic signatures to the calibration and alarm functions already found in AMS, Flowserve ValveAnalysis allows users to increase the flexibility of their Emerson system and preserve the value of their Flowserve equipment base.

With thousands of Flowserve valves installed in plants running AMS over Emerson distributed control systems (DCSs), Flowserve ValveAnalysis now gives users of AMS 6.0 or later a powerful new tool to evaluate the performance of those valves.

ValveAnalysis integrates with the Flowserve Logix 520si and 3200IQ HART positioners. Unlike similar competing software packages, ValveAnalysis does not bypass AMS, ensuring that a complete device history is always maintained.

Because ValveAnalysis does not unnecessarily duplicate the functionality already found in AMS, Flowserve is offering it to customers at an extremely cost-effective price.

Informative diagnostic tests that can be run with Flowserve ValveAnalysis include Ramp Signature and HDL. For positioners with actuator pressure management, the Ramp Signature test plots command versus position and compares this data to cylinder pressures.

The Ramp Signature test can be used to identify problems such as leaks in tubing fittings, improperly aligned plugs and seats, loose linkage, broken actuator springs, and sticky spool valves.

The ValveAnalysis HDL test calculates the four standard diagnostic signatures - hysteresis, deadband, repeatability and linearity - by opening and closing valves.

These signatures can be saved for future comparison to determine changes in equipment performance over time. HDL data can assist in making decisions that can improve maintenance procedures and maximise efficiency.

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