## 4 Discussion and Conclusions  
In the paper the most prominent techniques of the IFB selection developed in recent years have been tested for benchmark signals that imitate four different cases of the condition of the rotating component of the machine:  
1. the Gaussian White Noise, which corresponds to the vibration coming from bearings in the healthy condition,
2. the Gaussian White Noise with cyclic impulses, which corresponds to the local damaged bearing,
3. the non-Gaussian noise, which corresponds to the case without local damage (for the machine is in good condition and executes a specific technological process, e.g., crushing of the rock mass),
4. the non-Gaussian noise with cyclic impulses, which corresponds to the damaged bearing in the presence of impulsive noise, associated with the machine operation, e.g., local fault of bearing in the crusher. In case of the good condition of the machine, we should expect the \"flat\" distribution of the selector for each technique, whereas for damaged cases one should find some frequency band with a higher value of \"diagnostic feature\" (selector) than for other frequencies. In case 1, the values of all considered selectors are relatively small and do not significantly distinguish any frequency band. For damaged bearing (case 2), all \"impulse detectors\" point out frequency band where damage-related mechanical impacts excite structural resonance. Unfortunately, there is a high probability that strong impacts related to the technological process will also excite the same structures. Thus, in case of no damage (case 3), one will obtain a suggestion on the informative frequency band that will be a false alarm. Unfortunately, it is a drawback of all tested techniques. To be more precise, the kurtosis selector and kurtogram have 10 times larger values for the frequency band of the non-cyclic impulses than in case of the cyclic impulses of fault. Whereas Alpha selector, spectral Gini index, spectral smoothness index and infogram take similar values in both cases (case 2 and case 3). However, the CVB selector responds more than 17 times more strongly to impulses related to damage than to random impulses related to the operation of the machine. This is related to the definition of the CVB statistic. It omits a significant amount of non-cyclic impulses which fall into the tail of the amplitudes' distribution. For the last tested case (case 4), which is the most difficult, there are two types of impulsive (cyclic and non-cyclic) components in the signal. Almost all techniques are focused on the most impulsive component (related to the non-cyclic large observations). The CVB selector, recently proposed in [49]for machine diagnosis, is the unique solution that is based on the relation between amplitude ratio, i.e., the distribution of amplitudes of the background noise, where the predominant noise is Gaussian White Noise and cyclic impulses. Assuming that process-related impulses are much higher than the cyclic impulses, the CVB selector ignore them (they fall into the tail of the distribution) and search for smaller impulses that are cyclic in practice (however, our selector is blind to that property). In this paper we do not take into consideration the cyclostationary-based approach. However, our future plans are also related to this issue. When large non-cyclic impulses appear in the signal, then the classical cyclostationary methods cannot be applied. Most of them are based on the covariance (or coherence) function. For the impulsive signal, the theoretical covariance does not exist, thus the other measures of dependence need to be applied. Thus, our future plans are related to the application of the alternative measures of dependence to the classical cyclostationary-based methods. In our diagnostic approach, we always validate the efficiency of SOI extraction by classical envelope analysis. So, for case 3 (no damage), even if all techniques point out some frequency band, it will not be informative in the envelope spectrum (no component with fault frequencies).