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**Kurtosis Coefficient and Frequency Spectrum**
We have applied the function developed on the data set 172.mat downloaded from here. This data set corresponds to a signal of bearing faults at a speed rate of 1730 RPM, obtained at a sampling rate of 12000 samples/second (Fs), and a load defined as load 3. We have used 2 Hz and 4 kHz as cutoff frequencies for the bandpass filter. Next, we show the original signal with its kurtosis coefficient (Fig 2.a) and the frequency spectrum (Fig 2.b).

**Figure 2. (a) Time series original signal. (b) Spectrum**

**Figure 2. (a) Time series original signal. (b) Spectrum**

**Figure 4. Zoom at low frequencies**

**CONCLUSIONS**

A function written in MATLAB was developed to perform analyzes on bearing failure signals using a basic processing technique known as envelope analysis. This function was applied to a set of real data and its optimal functioning was verified by detecting the frequency components related to the faults (fundamental component and its harmonics). This function is generalizable. In fact, it can be applied to any set of bearing signal data to obtain output arguments with which a complete analysis can be made. You just have to be careful to properly define the input parameters such as the cutoff frequencies of the bandpass filter and the signal sampling frequency.