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Choosing the Correct Smoothing Window

LabVIEW 2013 Help

Edition Date: June 2013

Part Number: 371361K-01

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Selecting a smoothing window is not a simple task. Each smoothing window has its own characteristics and suitability for different applications. To choose a smoothing window, you must estimate the frequency content of the signal. If the signal contains strong interfering frequency components distant from the frequency of interest, choose a smoothing window with a high side lobe roll-off rate. If the signal contains strong interfering signals near the frequency of interest, choose a smoothing window with a low maximum side lobe level.

If the frequency of interest contains two or more signals very near to each other, spectral resolution is important. In this case, it is best to choose a smoothing window with a very narrow main lobe. If the amplitude accuracy of a single frequency component is more important than the exact location of the component in a given frequency bin, choose a smoothing window with a wide main lobe. If the signal spectrum is rather flat or broadband in frequency content, use the rectangular window, or no window. In general, the Hanning window is satisfactory in 95% of cases. It has good frequency resolution and reduced spectral leakage. If you do not know the nature of the signal but you want to apply a smoothing window, start with the Hanning window.

The following table lists different types of signals and the appropriate windows that you can use with them.

Type of Signal Window
Transients whose duration is shorter than the length of the window Rectangular
Transients whose duration is longer than the length of the window Exponential, Hanning
General-purpose applications Hanning
Spectral analysis (frequency-response measurements) Hanning (for random excitation), Rectangular (for pseudorandom excitation)
Separation of two tones with frequencies very close to each other but with widely differing amplitudes Kaiser-Bessel
Separation of two tones with frequencies very close to each other but with almost equal amplitudes Rectangular
Accurate single-tone amplitude measurements Flat top
Sine wave or combination of sine waves Hanning
Sine wave and amplitude accuracy is important Flat top
Narrowband random signal (vibration data) Hanning
Broadband random (white noise) Rectangular
Closely spaced sine waves Rectangular, Hamming
Excitation signals (hammer blow) Force
Response signals Exponential
Unknown content Hanning

Initially, you might not have enough information about the signal to select the most appropriate smoothing window for the signal. You might need to experiment with different smoothing windows to find the best one. Always compare the performance of different smoothing windows to find the best one for the application.


 

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