Millstrum analysis, Applications, Input signal requirements – Measurement Computing Medallion Rotate rev.2.3 User Manual

Page 39: Illstrum, Nalysis, Pplications, Nput, Ignal, Equirements

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October 2000

Medallion Rotate Manual

39

M

ILLSTRUM

A

NALYSIS

Millstrum analysis in Medallion Rotate Plus simplifies the process of

identifying families of harmonics and sidebands. Harmonics are multiples of a
primary frequency, and appear as a series of equally spaced spectral peaks of
increasing frequency. Sidebands are pairs of equally spaced spectral peaks that
appear to both sides of a primary frequency. Sidebands are often caused by
modulation of the primary (“carrier”) frequency by a second frequency.

In some cases, it can be difficult to identify harmonics and sidebands in a

conventional Spectrum plot—particularly in spectra that have many peaks
obscuring the harmonics or sidebands.

Millstrum analysis simplifies the process of identifying harmonics and

sidebands by removing everything that is not harmonic, and presenting the
results in an easily-understood format. Millstrum analysis is similar to using the
cepstrum, but goes further in simplifying the results so that you do not have to
perform any additional calculations. The fundamental frequency and
modulating frequencies appear clearly as peaks in the Waterfall plot from
Millstrum analysis.

A

PPLICATIONS

Millstrum analysis is ideal for identifying harmonics and sidebands in the

following applications:

Heavily modulated signals.

Low amplitude harmonics and sidebands, such as in early-stage
gearbox and bearing faults.

Signals that produce complicated spectra with peaks obscuring the
harmonics or sidebands.

I

NPUT

S

IGNAL

R

EQUIREMENTS

You can use Millstrum analysis on a data channel without a smoothed

machine speed curve; however, you will not be able to use the machine speed
or order tracking capabilities of the Millstrum plot.

Medallion Rotate processes the transducer data to create the Millstrum

analysis. When collecting the non-tachometer data (vibration, temperature, …),
note the following:

• If you want to see low frequency data in the Millstrum analysis, make

sure that the high pass filter setting in your analyzer is not excluding
the desired low frequencies.

• The sample rate in the analyzer must be at least 2.5 times the maximum

frequency of interest to avoid aliasing.

• When there is a tachometer signal, you can use the order domain for

easier identification of the periodic frequencies.

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