Datat Interpretation Spectrum Plots

- Whereas a Trend is amplitude values versus time, a "Spectrum" Plot is amplitude versus frequency
- A spectrum, a.k.a. an "FFT", allows you to assess severity (with the amplitude) and helps identify the source (with the frequency)

Vibration spectra provides important clues to machine problems. There are tools provided in all software packages that help with this analysis. The most important are:

- Moveable cursor - A "base" cursor that can be moved to any frequency and identifies the amplitude at that frequency.
- Harmonic cursors - Activating this tool creates additional cursors (as many as are required) that appear at integer multiples of the base cursor. If the base cursor is located at 1x rpm, harmonics will appear at 2x, 3x, 4x, etc. This is the most important analysis tool available. All harmonic cursors are at higher frequencies than the base cursor
- Sideband cursors - Activating this tool creates additional cursors at frequencies to either side of the base cursor. If the 1st (closest) sideband cursors are located 50 cpm to either side of the base cursor, additional sideband cursors (as many as required) will each be located an additional 50 cpm away. For instance, the 2nd sideband cursors will be 100 cpm away from the base cursor, the 3rd will be 150 cpm away, etc.

These three tools are sufficient for the beginner and for 99% of most analyses. There are, of course, other useful tools such as "labels" and frequency groups but that is more vendor specific and should be learned in a software class and through experience.

Remember, ALL spectral analysis is limited in its use and accuracy by the spectrum resolution.

Commonly used terms include:

- Fundamental Frequency - 1x rpm. Remember that a belt drive, for instance, has three fundamental frequencies
- Dominant Frequency - Frequency at which the highest amplitude occurs
- Synchronous Vibration - Vibration harmonically related to a fundamental frequency
- Non-synchronous Vibration - Vibration not harmonically related to a fundamental frequency
- Sub-synchronous Vibration - Vibration occurring at a frequency below the fundamental frequency

- The vibration is "sampled" (collected) over a pre-determined period of time
- Although sometimes a relatively simple sine wave, it will far more often be a complex signal with a number of different frequency components
- The complex signal shown below is made up of a 1x rpm component and a 5x rpm component (vane pass ?) being generated by the machine
- There can be, and usually are, far more influences - misalignment, bearing problems, soft foot, looseness, frequency modulation, amplitude modulation, and so forth

What the transducer actually 'senses' is an analog signal - one that mirrors the actual movement of the bearing at the location of the transducer.

The signal processing that follows the analog signal collection consists of a couple of mathematical processes:

- A/D converter - Converts the analogue signal to a digital one
- Fourier Transform - This process is based on the principle that any periodic signal (e.g. vibration) can be broken down into the trigonometric waves that created the signal. In practical terms, the principle means that the frequencies and associated amplitudes that created the signal can be 'backed out' and presented to the analyst on a spectrum plot

The FFT process is extremely complex when being applied to mechanical vibrations. Although a fairly reliable and useful tool, it MUST be understood that a spectrum is always suspect because these mathematical processes (A/D and FFT) often cause either or both of the following to happen:

- Vibration peaks get added (like sidebands and harmonics) that don't actually exist. That is not to say either are to be ignored - they can still provide valuable clues to the analyst
- Occurrences (events) that may be obvious when viewing the raw time domain signal are completely lost

For these reasons, it is strongly recommended that at the very least the time domain be used where it is most useful and the spectrum is the weakest:

- Slow Speed Equipment
- Gear Applications
- Sleeve (Plain) Bearings

The reasons for this lie in what the FFT process actually does and what factors influence its output (the spectrum).

- The spectrum shown here shows a few of the 400 amplitude ranges that make up this spectrum. This close up shows that the creation of a spectrum is actually similar to the children's game of 'connect the dots'
- Each frequency range in this spectrum is 30 cpm wide. Each red circle is labelled as an exact multiple of 30 except the peaks
- The frequency values shown at the tops of the peaks are able to be calculated more accurately
- The 'height' of each red circle is the amplitude for that frequency range. For instance, the value at 2130 is the amount of vibration mathematically calculated between 2101 - 2130 cpm
- The number of frequency ranges (amplitude values) is known as the "Lines of Resolution". Usually, this is 400 but can be higher or lower (100, 200, 800, 1600, 3200 and more)
- The maximum frequency shown on the plot is called the "Fmax"
- The width of each frequency range is called the "Spectrum Resolution"

The spectrum resolution (width of each frequency range) equals the Fmax divided by the Lines of Resolution.

- It is of crucial importance to understand spectrum resolution

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