Page 399 - Intro Predictive Maintenance

390 An Introduction to Predictive Maintenance

Monitoring the trends of a machine-train or process system will provide the ability to
prevent most catastrophic failures. The trend is similar to the bathtub curve used to
schedule preventive maintenance. The difference between the preventive and predic-
tive bathtub curve is that the latter is based on the actual condition of the equipment,
not a statistical average.

The disadvantage of relying on trending as the only means of maintaining a predic-
tive maintenance program is that it will not tell you the reason a machine is degrad-
ing. One good example of this weakness is an aluminum foundry that relied strictly
on trending to maintain its predictive maintenance program. In the foundry are 36 can-
tilevered fans that are critical to plant operation. The rolling-element bearings in each
of these fans are changed on an average of every six months. By monitoring the trends
provided by the predictive maintenance program, the plant can adjust the bearing
changeout schedule based on the actual condition of the bearings in a specific fan.
Over a two-year period, no catastrophic failures or loss of production resulted from
the fans being out of service. Did the predictive maintenance program work? In their
terms, the program was a total success; however, the normal bearing life should have
been much greater than six months. Something in the fan or process created the reduc-
tion in average bearing life. Limiting the program to trending only, the plant was
unable to identify the root-cause of the premature bearing failure. Properly used, your
predictive maintenance program can identify the specific or root-cause of chronic
maintenance problems. In the example, a full analysis provided the answer. Plate-out
or material buildup on the fan blades constantly increased the rotor mass and there-
fore forced the fans to operate at critical speed. The imbalance created by operation
at critical speed was the forcing function that destroyed the bearings. After taking cor-
rective actions, the plant now gets an average of three years from the fan bearings.

17.2 ANALYSIS TECHNIQUES
All machines have a finite number of failure modes. If you have a thorough under-
standing of these failure modes and the dynamics of the specific machine, you can
learn the vibration analysis techniques that will isolate the specific failure mode
or root-cause of each machine-train problem. The following example will provide a
comparison of various trending and analysis techniques.

17.2.1 Broadband Analysis
The data acquired using broadband data are limited to a value that represents the total
energy that is being generated by the machine-train at the measurement point location
and in the direction opposite the transducer. Most programs trend and compare the
recorded value at a single point and disregard the other measurement points on
the common-shaft.

Rather than evaluate each measurement point separately, plot the energy of each mea-
surement point on a common-shaft. Figure 17–1 illustrates this technique for a