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Reference Manual
00809-0100-4021, Rev GC
Section 4: FOUNDATION fieldbus Configuration
April 2014
Foundation™ fieldbus configuration
4.10.4 Statistical process monitoring (SPM)
SPM algorithm provides basic information regarding the behavior of process measurements
such as PID control block and actual valve position. The algorithm can monitor up to four user
selected variables. All variables must reside in a scheduled function block contained in the
device. This algorithm can perform higher levels of diagnostics by distribution of computational
power to field devices. The two statistical parameters monitored by the SPM are mean and
standard deviation. By using the mean and standard deviation, the process or control levels and
dynamics can be monitored for change over time. The algorithm also provides:
Configurable limits/alarms for High variation, low dynamics, and mean changes with
respect to the learned levels
Necessary statistical information for Regulatory Control Loop Diagnostics, Root Cause
Diagnostics, and Operations Diagnostics
Note
Fieldbus devices offer a wealth of information to the user. Both process measurement and
control is feasible at the device level. The devices contain both the process measurements and
control signals that are necessary to not only control the process, but to determine if the
process and control is healthy. By looking at the process measurement data and control output
over time, additional insight into the process can be gained. Under some load conditions and
process demands, changes could be interpreted as degradation of instruments, valves, or major
components such as pumps, compressors, heat exchangers, etc. This degradation may indicate
that the loop control scheme should be re-tuned or re-evaluated. By learning a healthy process
and continually comparing current information to the known healthy information, problems
from degradation and eventual failure can be remedied ahead of time. These diagnostics aid in
the engineering and maintenance of the devices. False alarms and missed detections may occur.
If a reoccurring problem in the process exists, contact Emerson Process Management for
assistance.
Configuration phase
The configuration phase is an inactive state when the SPM algorithm can be configured. In this
phase, the block tags, block type, parameter, limits for high variation, low dynamics, and mean
change detection can be set by the user. The “Statistical Process Monitoring Activation”
parameter must be set to “disabled” to configure any SPM parameter. SPM can monitor any
linkable input or output parameter of a scheduled function block that resides in the device.
Learning phase
In the learning phase of SPM, the algorithm establishes a baseline of the mean and dynamics of
a SPM variable. The baseline data is compared to current data for calculating any changes in
mean or dynamics of the SPM variables.
Monitoring phase
The monitoring phase starts once the learning process is complete. The algorithm compares the
current values to the baseline values of the mean and standard deviation. During this phase the
algorithm computes the percent change in mean and standard deviation to determine if the
defined limits are violated.
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