Abstract
Vibrations in rotating machinery are produced by a combination of periodic and random processes due to the machine's rotation cycle and interaction with the real world. The combination of such components can give rise to signals which have periodically time-varying ensemble statistics and are best considered as cyclostationary. In this paper, second-order cyclic statistical methods are described and several applications of these to machine vibration analysis are introduced. The second-order techniques are compared with traditional (purely stationary) spectral analysis and synchronous averaging (first-order cyclic analysis). This comparison is made for data collected from a rotating machine subjected to bearing faults and the applications are demonstrated.
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