Rockwell Automation Publication 1444-UM001D-EN-P - June 2018 153
Measurement Definition Chapter 4
FFT Window Type Select from:
•Rectangular
•Flat top
• Hanning
• Hamming
Select the window function to apply in the FFT signal processing.
• FFT Windows Purpose:
FFT Windows are applied to address the problem of signals that occur at
frequencies that are not centered within a frequency bin. In these cases,
energy from the signal can be dispersed among adjacent bins such that the
amplitude of neither bin represents the actual magnitude of the signal. For
example:
If no window is applied (the Rectangular Window): If the frequency of a signal
is precisely centered between bins, with no other signals present, then the
magnitude of each bin is precisely ½ that of the actual signal. When viewing
the FFT, two adjacent bins are presented with equal and comparatively small
peak amplitudes, rather than one bin with 2x that amplitude, which is the
actual amplitude of the signal.
As the frequency of the signal moves across a bin the proportion of its energy
that “bleeds” into adjacent bins changes. So, if using a Rectangular Window,
and a signal with a constant amplitude were to move 50...60 Hz (for
example10 bins) then a Waterfall display shows the bins growing as the
signal enters the bin, to a maximum equal to the actual signal amplitude,
when the signal was centered in the bin, and then falling to zero as the signal
moved above the bin.
FFT Windows are used to “smooth” this effect such that the amplitude of the
signal, as represented by the amplitude of the bin that it is in, is better
represented. But there are trade-offs as these techniques all tend to make it
more difficult to ascertain the specific frequency of a signal (which bin is it).
So when selecting an FFT Window the key is to understand the intent: Is it
more important to know the exact amplitude of the signals that the FFT
measures, or is it more important to know the exact frequencies of the signals
within the FFT?
• Available FFT Windows:
Rectangular
– Description: No window is applied
– Other Terms: Normal, Uniform
– Performance: Gives poor peak amplitude accuracy, good peak frequency
accuracy.
– Usage: Use this method only for transient signals that die out before the
end of the time sample, or for exactly periodic signals within the time
sample (such as integer order frequencies in synchronously sampled data).
Flat Top
– Other Terms: Sinusoidal
– Performance: Gives good peak amplitude accuracy, poor peak frequency
accuracy for data with discrete frequency components.
– Use this method when amplitude accuracy is more important than
frequency resolution. In data with closely spaced peaks, a Flat Top window
can smear the peaks together into one wide peak.
Hanning
– Description: A general-purpose window that is similar to a Hamming
window.
– Performance: Gives fair peak amplitude accuracy, fair peak frequency
accuracy.
– Usage: It is used on random type data when frequency resolution is more
important than amplitude accuracy. Most often used in predictive
maintenance.
Hamming
– Performance: A general-purpose window that is similar to a Hanning
window.
– Gives fair peak amplitude accuracy, fair peak frequency accuracy. It
provides better frequency resolution but decreased amplitude accuracy
when compared to the Hanning window.
– Usage: Use it to separate close frequency components.
Table 32 - Bands (continued)
Parameter Values Comments
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