Abstract
Statistical moments have been widely used for condition monitoring and diagnosis of rolling-element bearings. However, lower moments are less sensitive to incipient faults, whereas higher moments are over-sensitive to spurious vibrations and noise. Hence, the statistical moments used in practice are limited to kurtosis and third normalized moment of rectified data, i.e. Honarvar third moment Sr. In order to overcome the drawbacks of kurtosis and Sr, a class of new diagnostic indices have been derived from the viewpoint of Rényi entropy, to characterize the vibration signature. These new indices can be treated as a generalization of the traditional statistical moments, of which kurtosis and Sr are just two special cases. Numerical simulations and experiments have been conducted. The results show that these new indices are as effective as kurtosis and Sr in detecting the defect of a bearing, and that some of the new indices could provide a better compromise performance than kurtosis and Sr with respect to the sensitivity and the robustness.
