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FFT Function
For a large class of signals, you can gain greater insight by looking at spectral representation rather
than time description. Signals encountered in the frequency response of amplifiers, oscillator phase
noise and those in mechanical vibration analysis, for example, are easier to observe in the frequency
domain.
If sampling is done at a rate fast enough to faithfully approximate the original waveform (usually five
times the highest frequency component in the signal), the resulting discrete data series will uniquely
describe the analog signal. This is of particular value when dealing with transient signals, which
conventional swept spectrum analyzers cannot handle.
While FFT has become a popular analysis tool, some care must be taken with it. In most instances,
incorrect positioning of the signal within the display grid will significantly alter the spectrum,
producing effects such as leakage and aliasing that distort the spectrum.
An effective way to reduce these effects is to maximize the acquisition record length. Record length
directly conditions the effective sampling rate and therefore determines the frequency resolution and
span at which spectral analysis can be carried out.
Setting Up FFT
1. Follow the usual steps to
submenu.
2. Open the FFT subdialog.
3. Choose an Output type.
4. Optionally, choose a weighting Window (see below).
5. Depending on your Output Type selection, also make selections for :
Group Delay Shift
l
Line Impedence. By default, the FFT function assumes a termination of 50 Ohms. If an
l
external terminator is being used, this setting can be changed to properly calculate the
FFT based on the new termination value.
6. Check the Suppress DC box to make the DC bin go to zero. Otherwise, leave it unchecked.
Choosing a Window
The choice of a spectral window is dictated by the signal's characteristics. Weighting functions
control the filter response shape, and affect noise bandwidth as well as side lobe levels. Ideally, the
main lobe should be as narrow and flat as possible to effectively discriminate all spectral
components, while all side lobes should be infinitely attenuated. The window type defines the
bandwidth and shape of the equivalent filter to be used in the FFT processing.
Rectangular windows provide the highest frequency resolution and are useful for estimating the type
of harmonics present in the signal. Because the rectangular window decays as a (sinx)/x function in
the spectral domain, slight attenuation will be induced. Functions with less attenuation (Flat Top and
set up a math
function, selecting FFT from the Frequency Analysis
Math and Measure
115
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