Detection of corrosion in ball bearings through the computation of statistical indicators of stray-flux signals

Bearing failures are among the most common faults in induction motors. In industry, their detection is usually carried out through the analysis of vibration data. However, there are applications in which this technique cannot be used. In these cases, the use of alternative quantities is primordial to reach a reliable conclusion of the bearing condition. The analysis of current and stray-flux signals has been proposed as alternative way to diagnose the bearing condition; despite it has been proven the complexity of using these signals for reaching an accurate conclusion about the condition of the bearings, it has been also demonstrated their potential for obtaining very useful information for the diagnosis of these elements. This work proposes the computation of statistical indicators obtained from stray-flux signals to detect the presence of corrosion in bearings. It is proven the usefulness of some of these indicators not only to detect this fault but also to discriminate versus other failures. In the work it is also shown the superiority of using this approach with stray-flux signals compared to other electrical quantities with regards to the detection of the considered fault.