Page 111 - An Introduction To Predictive Maintenance

Predictive Maintenance Techniques 101

Figure 6–1 Vibration is dynamic and amplitudes constantly change.

tion profiles. Anti-aliasing filters are incorporated into the analyzers specifically
to remove spurious signals such as impacts or transients. Although the intent behind
the use of anti-aliasing filters is valid, their use can distort a machine’s vibration
profile.

Because vibration data are dynamic and the amplitudes constantly change, as shown
in Figure 6–1, most predictive maintenance system vendors strongly recommend
averaging the data. They typically recommend acquiring 3 to 12 samples of the vibra-
tion profile and averaging the individual profiles into a composite signature. This
approach eliminates the variation in vibration amplitude of the individual frequency
components that make up the machine’s signature; however, these variations, referred
to as beats, can be a valuable diagnostic tool. Unfortunately, they are not avail-
able from microprocessor-based instruments because of averaging and other system
limitations.

The most serious limitations created by averaging and the anti-aliasing filters are the
inability to detect and record impacts that often occur within machinery. These impacts
generally are indications of abnormal behavior and are often the key to detecting and
identifying incipient problems.

Frequency-Domain Data
Most predictive maintenance programs rely almost exclusively on frequency-domain
vibration data. The microprocessor-based analyzers gather time-domain data and auto-