145
Reference Manual
00809-0300-4750, Rev CA
March 2016
7.6
Explanation of signal processing algorithm
An example plotting flow rate versus time is given below to help visualize the signal
processing algorithm.
Figure 7-1. Signal Processing Functionality
X. Input flow signal from sensor
O. Average flow signals and transmitter output, determined by the
number of samples
parameter
Tolerance band, determined by the
percent limit
parameter.
Upper value = average flow + [(percent limit/100) average flow]
Lower value = average flow - [(percent limit/100) average flow]
1.
This scenario is that of a typical non-noisy flow. The input flow signal is within the
percent limit tolerance band, therefore qualifying itself as a good input. In this case
the new input is added directly into the running average and is passed on as a part
of the average value to the output.
2.
This signal is outside the tolerance band and therefore is held in memory until the
next input can be evaluated. The running average is provided as the output.
3.
The previous signal currently held in memory is simply rejected as a noise spike
since the next flow input signal is back within the tolerance band. This results in
complete rejection of noise spikes rather than allowing them to be “averaged” with
the good signals as occurs in the typical analog damping circuits.
4.
As in number 2 above, the input is outside the tolerance band. This first signal is
held in memory and compared to the next signal. The next signal is also outside the
tolerance band (in the same direction), so the stored value is added to the running
average as the next input and the running average begins to slowly approach the
new input level.
5.
To avoid waiting for the slowly incrementing average value to catch up to the new
level input, an algorithm is provided. This is the “time limit” parameter. The user
can set this parameter to eliminate the slow ramping of the output toward the new
input level.
Flow
rate
Time limit
10 samples = 1 second
Max
% limit
Time
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