Emerson 3051S Spezifikationen Seite 81

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Reference Manual
00809-0200-4801, Rev CA
July 2010
6-3
Rosemount 3051S
The sensing of the unique signature begins with the combination of a high
speed sensing device, such as the Rosemount 3051S Pressure Transmitter,
with software resident in a F
OUNDATION fieldbus Feature Board to compute
statistical parameters that characterize and quantify the noise or variation.
These statistical parameters are the mean and standard deviation of the input
pressure. Filtering capability is provided to separate slow changes in the
process due to setpoint changes from the process noise or variation of
interest. Figure 6-2 shows an example of how the standard deviation value ()
is affected by changes in noise level while the mean or average value ()
remains constant. The calculation of the statistical parameters within the
device is accomplished on a parallel software path to the path used to filter
and compute the primary output signal (e.g. the pressure measurement used
for control and operations). The primary output is not affected in any way by
this additional capability.
Figure 6-2. Changes in process
noise or variability and affect on
statistical parameters
The device can provide the statistical information to the user in two ways.
First, the statistical parameters can be made available to the host system
directly via Foundation fieldbus communication protocol or FF to other
protocol converters. Once available, the system may make use of these
statistical parameters to indicate or detect a change in process conditions. In
the simplest example, the statistical values may be stored in the DCS
historian. If a process upset or equipment problem occurs, these values can
be examined to determine if changes in the values foreshadowed or indicated
the process upset. The statistical values can then be made available to the
operator directly, or made available to alarm or alert software.
Second, the device has internal software that can be used to baseline the
process noise or signature via a learning process. Once the learning process
is completed, the device itself can detect significant changes in the noise or
variation, and communicate an alarm via PlantWeb alert. Typical applications
are change in fluid composition or equipment related problems.
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