Perceptive analysis of bearing defects (Contribution to vibration monitoring)

Abstract

The objective of this article is to improve bearing monitoring via vibration indicators, by developing combinations of indicators, which is more effective than using isolated classical indicators. We use a new perceptive approach to seek correlations between vibration analysis and the perception of noise generated by the defects of rotating machines. Therefore, an experimental bench was developed to simulate machine defects (bearings, alignments and gears) and to perform vibration and acoustic measurements. This study was split into three stages: the first was to process the signals of simulated defects using different vibration analysis techniques (scalar indicators and spectral analysis). The second phase was devoted to a perception test of the noises generated by the simulated defects; this test was carried out on different auditors. The results obtained from the perception test were then processed using multidimensional analysis (MDS), to calculate the dimensions of the sound perception space. The final stage of this study consisted in searching the dimensions correctly representing the deterioration of the simulated defects, and in correlating these subjective dimensions with objective classical indicators (RMS, Kurtosis, Crest factor, CGS, etc.), to define more sensitive indicators calculated from combinations of classical vibration indicators.