When it comes to flowmetering systems in your facility, what is the best way to measure its true performance?
Karl Stappert
Flow Solutions Advisor
In a Flow Control magazine article, R & R: How reproducible is your highly repeatable metering system?, Emerson’s Karl Stappert, of the Flow Solutions team, addresses these important concepts—repeatability and reproducibility.
Karl opens defining the two terms. Repeatability is the sensor’s ability to provide the same flow indication [repeatedly] at unchanging process conditions. These conditions include flow rate, fluid properties, temperature, and pressure to name a few. He defines condition of repeatability: a condition, out of
…a set of conditions, that includes the same measurement, same operating conditions (process and ambient), same location, and replicate measurements on the same object over a short timeframe.
Measurement device product specifications:
…often called accuracy, is achieved under specific conditions of repeatability.
The issue is, of course, that operating plants rarely have these conditions of repeatability. Unlike a calibration laboratory, they are constantly changing. Karl notes that repeatability is one of the most discussed statistical quality measures used for measurement instruments and that turbine meters are one of the most repeatable flow measurement technologies available.
He shares that if repeatability were the key consideration, then turbine meters should be the meter of choice among metrology [science of measurement] experts. They are not.
Repeatability performance statistics do not factor in the influence quantities. An influence quantity is an influence that does not affect the quantity that is being measured, but affects the output of the system performing the measurement. Common influences are a change in temperature and pressure (process and ambient), fluid property (density, viscosity), flowrate, or installation conditions (piping, valves, meter orientation).
Reproducibility is a performance statistic that gives an indication of a measurement system’s immunity to influence quantities. Karl defines reproducibility as:
…the ability of a measurement system, over a changing set of conditions, to replicate the same measurement. A statement of reproducibility should include the conditions changed and unchanged.
He illustrates examples of highly repeatable measurements that are less reproducible over changing conditions than other measurements with lower repeatability. Technologies have advanced to provide active correction to changing conditions. The compensation improves reproducibility but some flow measurement technologies are more reproducible than others. One example highlighted is Coriolis flow measurement:
Its list of beneficial attributes is considerable and includes no wearing parts and high insensitivity to flow profile, density, viscosity, velocity, temperature, and pressure change. In fact, if an evaluation of the technology’s reproducibility based on broad changes in process and fluid property conditions is performed, the technology’s performance far exceeds that of any traditional technology.
Another example is multi-path ultrasonic meters, which:
…have the ability to actively measure flow velocity profiles (swirl, asymmetries, high and low Reynolds number), and compensate for change in these affects.
Karl concludes:
The users of metering technologies can acquire a great deal of insight into the cause of unacceptable variations in their measurement systems and methods to improve their processes by evaluating the reproducibility of the measurement systems. In most instances, users will be better served asking the question, “How reproducible is my measurement system?” than utilizing repeatability alone as the gatekeeper of low uncertainty measurement.
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