As we’ve discussed, you can draw upon many tools to develop an effective CM program. But don’t overlook or underestimate the human factor. Routine checks and observations by operators and maintenance technicians can yield valuable subjective data. In addition, consider partnering with an experienced specialist; such a firm can add perspective, introduce the latest technology, offer oversight and provide training necessary to maximize results.
Tips and traps
In implementing CM techniques, the first rule of thumb is to be sensitive to in-house levels of experience. Because many maintenance staffs aren’t expert on such methods, here’re some practical pointers.
- Recognize the vast differences between detecting a machinery problem and analyzing the cause. For example, installing a new bearing to replace one that indicates a high level of vibration may or may not be the solution to bearing failure. Usually, a secondary issue is the primary contributing factor. Such root causes could include misalignment, looseness, imbalance or others; proper analysis will drill down to the right solution.
- Specify sufficient frequency range. The range should be high enough to capture all defect frequencies of interest. For example, sleeve bearing equipment typically is measured to a frequency range of 20 times running speed and rolling element bearing equipment typically is measured to 50 or 60 times running speed.
- Carefully select the measurement point. When collecting machinery vibration data, avoid painted surfaces, unloaded bearing zones, housing splits and structural gaps. These areas cloud response and compromise data integrity. Take measurements at the same precise location for comparison and, when measuring vibration with a hand-held sensor, pay close attention to sensor position, angle and contact pressure.
- Optimize the conditions. Ideally, take measurements while a machine is operating under normal conditions — for example, when the rotor, housing and main bearings are at their regular steady operating temperatures and the machine’s running speed is within the manufacturer’s specifications (rated voltage, flow, pressure and load). For variable-speed equipment, take measurements at the same point in the process or manufacturing cycle. Periodic measurements at all extreme rating conditions can confirm the absence of outlying problems that only appear at extreme conditions.
5. Check equipment status. Make sure the measuring equipment collecting vibration data is in good condition and the transducer has sufficient time to settle after initial power-up.
FFT spectrum analysis:
- Minimize spectral leakage. Applying the FFT method to finite-duration sequences can fall short due to “spectral leakage.” This effect occurs when the signal doesn’t result in a sequence containing the whole number of periods. By applying weighted “windows” to the data sample under review, you can plug such leaks. Caution: while weighted windowing (configured as rectangles, triangles or others) can improve the quality of a spectrum in particular cases, some distortion may still occur.
- Factor in appropriate resolution settings. The FFT frequency spectrum has some basic settings that determine the usability of the data. The FFT is collected with a given resolution that is defined by the frequency span being measured divided by the number of bins or lines collected. Closely spaced defect frequencies may require higher resolution to distinguish. As resolution is raised, the amount of time necessary to collect the data increases.
Time domain analysis:
Establish appropriate measurement intervals. Conventional thinking holds that vibration signals from rotating machinery are stationary and continuous. This implies that the vibration signal is the same from rotation interval to rotation interval, which may not be true. Many impulsive responses will change in amplitude or slide rather than roll over a defect. So, determine a suitable measurement time (typically encompassing 10 to 15 rotations) for the machinery.