Collecting useful information for spectrum analysis
FFT spectrum is an incredibly useful analysis tool. If a machinery problem exists, FFT spectra provide information to help determine the location of the problem, the cause of the problem and, with trending, how long until the problem becomes critical. But certain information is needed before attempting to diagnose an FFT spectrum. Below are tips for collecting that information.
1. Identify all components of the machine that could cause vibration
- If the machine is connected to a fan or pump, know the number of fan blades or impellers
- If bearings are present, know their bearing defect frequencies
- If the machine is connected to gears, know the number of teeth for each gear
- If the machine is driven with belts, know the belt lengths
- Is the machine operating in the same vicinity as another machine? If so, know the running speed of the adjacent machine. Vibration from one machine can travel through the foundation or structure and affect vibration levels on an adjacent machine
- Is the machine mounted horizontally or vertically?
- Is the machine overhung or connected to anything that is overhung?
2. Identify the machine’s running speed
Knowing the machine’s running speed is critical when analyzing an FFT spectrum. There are several ways of determining running speed.
- Read the speed from instrumentation at the machine or from instrumentation in the control room monitoring the machine
- Look for peaks in the spectrum at 1 800 or 3 600 r/min if the machine is an induction electric motor (1 500 and 3 000 r/min for 50 Hz countries). Electric motors usually run at these speeds
- An FFT’s running speed peak is “typically” the first significant peak reading the spectrum from left to right. Look for this peak and check for peaks at two times, three times, four times, etc., the suspected running speed frequency (2x, 3x, 4x). Harmonics usually cause vibrations at multiples of the running speed frequency (although they might be very small)
3. Identify what type of measurement produced the FFT spectrum
- Was it a displacement, velocity, acceleration, enveloping, SEE, etc., measurement that produced the spectrum?
- Where was the probe positioned: horizontal, vertical, axial, in the load zone?
4. If possible, obtain any historical machinery data
- Are previously recorded values, FFTs or overall trend plots available?
- Was a base-line recorded?
Once you have collected as much of this information as possible, it’s time to move on to analyzing the spectrum. This process is outlined in the next article: Analyzing the spectrum using the process of elimination.