Higher-order time-frequency analysis and its application to fault detection in rotating machinery

Impulsive acoustic and vibration signals within rotating machinery are often induced by irregular impacting. The detection of these impulses can be useful for fault diagnosis purposes. Recently there has been an increasing trend towards the use of higher-order statistics for fault detection within mechanical systems based on the observation that impulsive signals tend to increase the kurtosis values. This paper considers the use of the third- and fourth-order Wigner moment spectra, called the Wigner bi- and tri-spectra respectively, for analysing such signals. Expressions for the auto- and cross-terms in these distributions are presented and discussed. It is shown that the Wigner trispectrum is a more suitable analysis tool and its performance is compared to its second-order counterpart for detecting impulsive signals. These methods are also applied to measured data sets from a car engine and an industrial gearbox. (C) 1997 Academic Press Limited.