The Analyzer Module
How to Collect Standard Vibr
ation Measurements
dB Reference
- Select the reference value to associate with the measurement
for calculations [i.e.,
20 Log (value/reference)]
dB Ref Units
– (
g
,
mg
, or
μg
) Select the appropriate dB units for the
measurement (e.g., to avoid having to type in a lot of zero's (i.e., 0.000001g),
you may select 1
μg
.
Detection –
Determines signal detection and scaling. Choose from:
RMS
– The
R
oot
M
ean
S
quared overall calculated from the FFT or time data.
Peak
– Scaled from RMS as
√
2
⋅
RMS.
PkPk
– Scaled from RMS as 2
⋅
√
2
⋅
RMS.
True Peak
– Detected from the time waveform rather than the FFT spectrum
as ½ (max Pk. – min Pk.).
True PkPk
– Detected from the time waveform rather than the FFT spectrum
as (max Pk. – min Pk.).
Lines –
Specify the spectrum’s lines of resolution. Note
- increased resolution requires
increased time for data collection and consumes more storage memory. Maximum
resolution is 25600 lines for a single channel measurement, 12800 lines for a 2
channel measurement,
or 6400 Lines for 3 and 4 channel measurements.
Avg. Type –
O
ptions available are either
RMS, Exponential,
or
PkHold.
RMS
– The summation of the magnitude of each spectral line is divided by the
total number of averages (ensemble averaging). This is the most frequently
used method of averaging for routine data collection and analysis.
Exponential
-
With exponential averaging,
the Microlog continuously averages
readings to minimize the noise level. Press the
Stop
function button to pause
the acquisition process, then press
Start
to continue acquisition.
Peak Hold
–
Peak Hold holds the highest value received at each spectral line
during the averaging time. This method of averaging is very useful when the
signal contains a great deal of amplitude variation and the primary objective of
the analysis is to see the maximum reached by each component.
Num. Averages – Averages
– Determines the number of average samples taken for
the measurement. Enter the number of FFT averages to be collected (from 1 to 4096).
Four to six averages are adequate and are normally used for machine monitoring. The
higher the number of averages, the slower the data collection.
Overlap
–
Overlap processing is advantageous when the time required to gather a time
record is much longer than the time needed to calculate an FFT spectrum. In the
Microlog, this occurs at frequencies below 1,000 Hz (60,000 CPM).
For lower frequencies, the amount of overlap can be increased to reduce the time
required to collect a given number of averages. Recognize, however, that the greater
the overlap, the more information shared between averages.
Overlap processing is used to obtain enough new ensembl
e data for an accurate
average. If the maximum frequency is low and the FFT process time is fast, the average
sum would include a high percent of old data with maximum overlap.
Below 2 kHz, 50% overlap and six averages is a reasonable
ROUTE setup.
SKF Microlog - GX Series
4 - 11
User Manual
