Again as I said RMS is of little use with gE, always use peak or if possible true peak.
the reason for this is impacting get avergaed out and are of little use.
Please find from skf technical newsletter.
gE why not to average.
Fast Fourier Transform (FFT) relies on a signal consistently repeating itself with time and averaging is used for standard Condition monitoring as it allows the data to become more statistically correct. However the process of averaging when applied to gE readings actually damages the data – Why? Bearing defect frequencies can be looked at as random signals in our data block as they do not happen synchronously with other rotational characteristics. Averaging exponentially reduces random frequencies with each average so we are potentially exponentially removing the bearing fault frequencies with every average applied.
One long FFT is much better than several quick overlap averages. In addition to this, the averaging process uses overlapping. This process allows us to reuse a percentage of the last signal block as the first corresponding percentage the signal in the second data block speeding up data acquisition 50% has become the standard overlap when averaging data. This reuse of the signal can make the bearing signals appear even more random and removed in the average process.
Rms V Peak/True Peak.
The choice of amplitude descriptor (detection type) also has a large effect on the quality of the data. If we look at a typical data block in the time domain (picture below), we can see some tall peaks due to short duration impacts - potentially bearing defects? If we use an RMS amplitude descriptor, then we sum the individual values and reduce the measured level to a much lower calculated value. Individual peaks would have to grow massively before they have an impact on the RMS value. If we select to use Peak or Peak-to-Peak then we are still not capturing the data correctly, as these two descriptors are calculated from the RMS value (Pk =1.414* RMS) (Pk-Pk = 2 *Peak) The correct way to look at this data is with a TRUE Peak detector as used in the Microlog