## 5 Results and Discussion  
By applying the FT to the current signal of the generator under study, Figure 2a,b are obtained for one and three phases, respectively. In the graphs, harmonics with frequencies of 40, 42, 46 and 56 Hz can be distinguished, which, according to references [42; 76; 90], are related to stator failures, broken bars, and phase imbalance. In addition, as described in reference [42], rotor failures are manifested by harmonics of the fundamental frequency (3, 5, 7, etc. ), which reinforce the indications of bar failure. \begin{table}
\begin{tabular}{c c} \hline
**Brand** & **NEG Micon** \\ \hline Model & NM 52/900 \\ \hline Rotor diameter & 52.2 m \\ \hline blades & 3 \\ \hline Power & 900 kW \\ \hline Power control & Stall control \\ \hline Drive train & \
\begin{tabular}{c} Gearbox type: Planetary-Parallel \\ Transmission ratio: 1:67.5 \\ Main bearing: spherical rollers \\ Cooling system: refrigerant, heat exchanger and pump \\ \end{tabular} \\ \hline Electric Generator &
\begin{tabular}{c} Type: SCIG \\ Speeds: 750/500 rpm \\ Poles: 4/6 \\ Power: 900 kW/200 kW \\ Voltage: 690 V/50 Hz \\ Cooling system: water \\ \end{tabular} \\ \hline Coupling to the power grid & Smooth, using thyristors \\ \hline \end{tabular}
\end{table} 
Table 1: Technical characteristics of the WT and electric generator. Figure 1: Location of the current clamps on the WT power panel. The frequency components are very close to the central frequency, and depending on the window used, the width of the lobes can be very large, and the identification of faults by means of the FFT is difficult, making it necessary to resort to other variables and techniques such as the power spectral density (PSD) [91]. In MATLAB, we obtain an improved version of the PSD, which is shown as a Welch periodogram (see Figure 3). In this approach, by definition, MATLAB applies the Hamming window and displays the part of the graph corresponding to the real values. Unlike the case of the classic FT, in the spectrum obtained by the Welch periodogram, a greater number of frequency peaks can be distinguished, such as 30, 46, 54, 63, 124, 165, 261, 451, 534, 575, and 781 Hz. Although the composition of the spectrum is uniform, there are differences in the magnitudes of the components. These differences can also be observed when comparing the three phases of the generator (see Figure 3b). Figure 2: FT of the WT current signal. (**a**) One phase and (**b**) three phases. Another alternative to overcome the drawbacks mentioned so far is the proposed methods to eliminate frequencies that are not of interest so that it is easier to identify the components sought. In this context, one option is the technique known as cepstrum analysis, which calculates the inverse FT of the signal spectrum on a logarithmic scale. Failures alter the rotor speed and magnitude of the components, creating new frequency components that have their own harmonic families. The cepstrum provides an average of each of these families displayed as a single line with their respective harmonics bands. Identifying the frequency of each frequency also allows for the separation of signals that have been combined due to convolution [53; 92]. By applying cepstrum analysis and selecting the appropriate scale for the axes, Figure 4 is obtained. Several families of components close to the fundamental wave can be more clearly distinguished than before. For our case, the harmonic families separated by 200 ms that are equivalent to 5 Hz are easily visible. These frequencies are consistent with a fault attributed to broken bars, as was deduced with the previous techniques. Other types of mechanical failures associated with these frequencies are imbalances of the blades and bearings of the generator, which, according to reference [93], are manifested by frequencies of 10 and 5 Hz, respectively.