Fault Detection in Ball-bearings Using Wavelet Variance
نویسنده
چکیده
This paper introduces a wavelet based, nonparametric statistical method for the detection of characteristic signals embedded in noise-polluted vibrational response signals. A case study is described in which this technique is applied to the task of identi~ying localised defects on the raceways of the roller bearings inside an automotive gearbox, assuming that during operation a transient impulse is generated each time a rolling elements passes over a defect. Using orthogonal wavelet analysis, it is possible to estimate the Signal-to-Noise Ratio (SNR) of measured signals. Large values of the SNR at different wavelet scales indicate the existence of transients and, by employing a statistical index based on wavelet variance to experimental data, it has been possible to identify the bearing defects present in the gearbox tested.
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