Page 157 - Intro Predictive Maintenance
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148       An Introduction to Predictive Maintenance

         From these time traces, the vertical impact appears to be stronger than the horizontal.
         In addition, the impact repeated at 0.015 and 0.025 seconds. Two conclusions can be
         derived from this example: (1) the impact source is a vertical force, and (2) it impacts
         the machine-train at an interval of 0.010 seconds, or frequency of 1/0.010 seconds
         equals 100Hz.

         The waveform in Figure 7–18 illustrates theoretically the unique frequencies and tran-
         sients that may be present in a machine’s signature. Figure 7–18a illustrates the com-
         plexity of such a waveform by overlaying numerous frequencies.  The discrete
         waveforms that make up Figure 7–18a are displayed individually in Figures 7–18b
         through 7–18e. Note that two of the frequencies (c and d) are identical but have a dif-
         ferent phase angle (f).

         With time-domain data, the analyst must manually separate the individual frequencies
         and events that are contained in the complex waveform. This effort is complicated
         tremendously by the superposition of multiple frequencies. Note that, rather than over-
         laying each of the discrete frequencies as illustrated theoretically in Figure 7–18a,
         actual time-domain data represents the sum of these frequencies as was illustrated in
         Figure 7–17.

         In order to analyze this type of plot, the analyst must manually change the time scale
         to obtain discrete frequency curve data. The time interval between the recurrences of
         each frequency can then be measured. In this way, it is possible to isolate each of the
         frequencies that make up the time-domain vibration signature.

         For routine monitoring of machine vibration, however, this approach is not cost effec-
         tive. The time required to manually isolate each of the frequency components and
         transient events contained in the waveform is prohibitive; however, time-domain data
         have a definite use in a total-plant predictive maintenance or reliability improvement
         program.

         Machine-trains or process systems that have specific timing events (e.g., a pneu-
         matic or hydraulic cylinder) must be analyzed using the time-domain data format.
         In addition, time-domain data must be used for linear and reciprocating motion
         machinery.


         Frequency-Domain
         Most rotating machine-train failures result at or near a frequency component associ-
         ated with the running speed. Therefore, the ability to display and analyze the vibra-
         tion spectrum as components of frequency is extremely important.

         The frequency-domain format eliminates the manual effort required to isolate the com-
         ponents that make up a time trace. Frequency-domain techniques convert time-domain
         data into discrete frequency components using a mathematical process called Fast
         Fourier Transform (FFT). Simply stated, FFT mathematically converts a time-based
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