Gear Fault Diagnosis Using Cyclic Bispectrum

This paper introduces the theory of cyclic statistics as a powerful tool for the diagnosis of gear faults. More precisely, a new method based on the cyclic bispectrum, a third order cyclic statistical function, is used for monitoring. This estimator furnishes a valuable means of detecting and characterising non-linear coupling effects as well as any periodic correlation between different components in machines. Therefore, the cyclic bispectrum provides much more combined information than classical methods such as spectrum and cepstrum analysis. Application to the diagnosis of spalling of the gear teeth of the U.S. Navy helicopter demonstrates the effectiveness of this new parameter for a good diagnosis. Copyright © 2002 IFAC