Frequency resolution calculator2/23/2023 Threshold value monitoring of averaged magnitude spectra is to be implemented. A sample configuration is described below. The concept described above can be implemented conveniently with the TwinCAT Condition Monitoring Library through parameterization of the function blocks provided. The averaging of adjacent frequency bins is largely equivalent to the averaging of spectra over time, but more computationally complex. For this purpose, the FFT should understandably be calculated at a higher frequency resolution than in the method of successive averaging of spectra over time described above. the averaging of adjacent frequency bins. This reduces the uncertainty of the determined values and makes a threshold analysis more reliable.Īn alternative method is the averaging of the calculated Fourier coefficients via the frequency, i.e. It makes sense to form several magnitude spectra and analyze them statistically, e.g. Statistical evaluation of the magnitude spectrum In the following, an evaluation based on the mean of several spectra is considered as an example. The parameters determined in this way are significantly more robust against interference and easier to assess visually. This approach presupposes the temporal stability or cyclic repetition of the signal to be analyzed. To compensate for this, the magnitude spectrum is usually averaged or evaluated by quantiles, see Statistical analysis. Therefore, the Fourier-transformed real noisy signals are usually not well suited for direct analysis or evaluation. The Fourier spectrum is very sensitive to noise and interference in the signal. When using special variants of the spectral calculation, several points can be optimized. Note: The above points refer in particular to the use of the FB_CMA_MagnitudeSpectrum and FB_CMA_PowerSpectrum.
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