# Bearing Severity Fault Evaluation Using Contour Maps--Case Study
## 4 Discussion and Conclusions  
In this work, a methodology was developed to represent the levels of failure of a bearing by means of contour maps which relate the level of failure, the frequency and its amplitude as a function of isolines. This methodology was applied to a real case of experimental acceleration measurements from a bearing test bench. Furthermore, within these contour maps, the points of registers other than those used for their generation were represented, observing coherence in all analysed cases. Therefore, the results suggested that this methodology can help in the prediction of bearing failures. The data presented were analysed by envelope analysis in different filter bands, which showed the influence on the identification by the specific bands, in cases of diagnostic confusion, such as that which occurred for failure level 2 at 350 rpm and 500 rpm. Another important feature to highlight is the increased diagnostic accuracy for high-level (3 and 4) failure cases evaluated at 500 rpm. Table 8 summarises the study conditions of the analysed cases described in Section 3, where it is observed that the threshold value is closely related to the rotational speed, fault level, filter band and the window width employed in each analysis. The filter bands used in this analysis are those proposed in a previous study [16]. The width of the analysis window corresponds to the time spent at each determined rotation speed for turning a total of 17.5 turns. The threshold value is determined with the criteria described in Section 2.5.1 and depends on the vibration index at each fault level. A clear advantage of the implementation of contour maps in fault diagnosis is the significant data reduction, which depends on the correct identification of the threshold, by suppressing the data associated with noise. Furthermore, when analysing the harmonics associated with the failure frequency, the importance of the behaviour of the isolines was demonstrated: for the same frequency, there are amplitudes associated with different levels of failure--that is, the relationship between frequency and amplitude with the level of failure is not biunivocal--which explains the difficulty of identifying the level of failure according to which frequency is being analysed. This methodology makes it possible to identify isoline behaviour patterns, establishing frequency sections associated with harmonics, to unambiguously study the evolution of a bearing failure. The proposed method allows classifying the level of bearing failure using many points (intersection between the value of the isolines and the amplitude of the frequency and its harmonics). Based on the preliminary results, the proposed direct calculation method has been quite accurate in its diagnosis. Although this method requires an operational history, it has several advantages compared to indirect diagnostic methods based on artificial intelligence. On the one hand, the analysis is deterministic, allowing an easy interpretation of the results by the analyst and thus, ruling out uncertainty in decision-making, such as what happens in the black box in neural networks. Also, since no prior training is required, it is not necessary to label a large amount of data. The presented treatment is generic and could be used in the monitoring of a wide range of mechanical equipment, where the