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Vibration Monitoring and Analysis  149





























                   Figure 7–19 Typical frequency-domain signature.


            trace into a series of discrete frequency components (see Figure 7–19). In a frequency-
            domain plot, the X-axis is frequency and the Y-axis is the amplitude of displacement,
            velocity, or acceleration.

            With frequency-domain analysis, the average spectrum for a machine-train signature
            can be obtained. Recurring peaks can be normalized to present an accurate represen-
            tation of the machine-train condition. Figure 7–20 illustrates a simplified relationship
            between time-domain and frequency-domain analysis.

            The real advantage of frequency-domain analysis is the ability to normalize each
            vibration component so that a complex machine-train spectrum can be divided into
            discrete components.  This ability simplifies isolation and analysis of mechanical
            degradation within the machine-train.

            In addition, frequency-domain analysis can be used to determine the phase relation-
            ships for harmonic vibration components in a typical machine-train spectrum. Fre-
            quency-domain normalizes any or all running speeds, where time-domain analysis is
            limited to true running speed.

            Mathematical theory shows that any periodic function of time,  f(t), can be repre-
            sented as a series of sine functions having frequencies w, 2w, 3w, 4w, and so on. Func-
            tion f(t) is represented by the following equation, which is referred to as a Fourier
            Series:

                                                    f
                                                                  f
                     ft () =  A +  A 1 sin (w t + )+  A 2 sin (2w t + )+  A 3 sin (3w t + )+ ...
                                      f
                                                                   3
                                                     2
                                       1
                           0
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