Measurement Computing Medallion Rotate rev.2.3 - Manual (Page 24)

24
Medallion Rotate Manual October 2000
E
XAMPLE
The following example is taken from a rolling mill. As the sheet of metal is
rolled out, the speed of the sheet increases. This produces a distinctive speed
profile, as shown in the data collected from several stands along the mill.
This plot is the raw DC tachometer signal.
1. The first step is to process the tachometer signal to create a smoothed
speed curve. For the steps to process a tachometer signal, see “Process
a Tachometer Signal.”
2. Repeat the first step to get smoothed speed curves for each stand.
3. Overlay the speed curves from different stands to see the speed profile
for the machine. You can overlay multiple speed curves by selecting
them in the Channel List window then clicking the Plot button.
T
HEORY
Medallion Rotate uses a spline-curve fit algorithm that computes raw or
initial estimates of a machine’s instantaneous rotating speed by utilizing
sampled analog data from the sensor. With pulse tachometer data, Medallion
Rotate computes an initial estimate by measuring the time between pulses. Next,
it uses a series of cubic splines that enforce continuity at their boundaries to
create a smooth estimate of the machine’s rotating speed.
Medallion Rotate then uses a unique technology to remove the “outliers”
from the raw estimate before re-evaluating the spline fit. This allows you to use
noisy tachometer signals or tachometer signals with dropouts. In some cases,
this can delay the need to repair or replace the tachometer.
x 5 = 50 samples/second