## 5 Results and Discussion
### Results for the IM Operating at 20 Hz
Moreover, the filter time response can become high due to the estimation process, leading to wrong results in signals with frequency variations. Another different technique is the phase-locked loop (PLL), which also allows to determine a single frequency and phase of any signal [37]. The problem with this technique is that it is prone to error when it operates in unbalanced conditions; moreover, if the amplitude is required, a different technique must be implemented for detecting it. Although these methodologies could be used to perform a FFC suppression, the GA is the only methodology that can estimate the three parameters in a single run, and it suppresses only one frequency component instead of a narrow frequency band and that is why its use is preferred. On the other hand, the GA is a heuristic and not a deterministic technique. In this sense, it can be considered as a grey-box approach where the input-output relationship is modeled through the objective function which turns out to be a pure sinusoidal wave. This type of approach provides some benefits compared with other methodologies like ANNs which act as black-box models. The main issue related to the use of the ANN relies in the fact that there is no model that relates the output with the input, therefore, the delivered results may present a lack of physical meaning or context, leading to a high uncertainty in the result interpretation [38]. Additionally, the ANN requires an exhaustive training process, thus, a huge amount of data from all the conditions under test must be previously acquired. In this sense, the GA is more suitable in this work because it does not require this training process. Moreover, the ANN results are more helpful in applications where an automatic classification is carried. This is a situation that goes beyond the scope of this work. In addition, it has to be said that there are some other optimization techniques like the global-local optimization technique used in [38] which can also perform the estimation of the FFC parameters. The global-local optimization technique fuses the use of a GA algorithm for finding the global optimal with the Quasi-Newton method for identifying local optimal solutions. One of the aims of this work consists of developing a simple preprocessing technique. Moreover, for this particular case, only the global optimal is required, thus the use of a different technique for finding local optimal would only introduce unnecessary complexity and computational burden. As in the case of the IM operating at 31 Hz, a total of 15 tests are performed to show the consistency of the results. The results of the LSH are used for conforming the boxplots of Figure 6. This time, it is observed that when the MCSA is used, the trend is contrary to what is expected because the highest amplitudes are measured when the IM operates at low load (see Figure 6a). Additionally, when the IM operates at medium load, the amplitudes of the LSH fall between 0.04 and 0.061 A, whereas for the case of the IM operating at high load, the amplitudes appear between 0.017 and 0.041 A. Therefore, all the amplitudes that describe the medium load fault condition are contained in the group for the high load condition and it is not possible to discriminate from one group to another. The NF-MCSA methodology improves the results a little, and the groups are compact, indicating that the differences among the amplitude measurements are low. However, the highest amplitudes are presented when the IM operates at medium load, which is not the expected behavior either (see Figure 6b). In this case, it is observed that the three groups have values in the range comprised between 0.021 and the 0.023 A, i.e., there exists overlap among the three operative conditions. As explained before, this problem is originated by the spectral leakage that exists around the FFC. The leakage affects the amplitude of the failure harmonics, causing the conventional MCSA technique and the NF-MCSA to not properly identifying the failure severity.