Vibration-based fault detection of sharp bearing faults in helicopters

Many signal processing tools have been developed by the mechanical and signal processing community to find the characteristic symptoms of sharp bearing faults (like localized spalling) from vibratory analysis. However the context of helicopter imposes a limited sampling frequency regarding the observed phenomena, many noisy vibrations and flight regimes. The performances of the classical methods are limited in such an environment mainly in identifying fault frequencies. Local bearing faults induce temporal periodic and impulsive patterns that produce redundant harmonics in the spectral domain. In this article four methods are proposed to take advantage of that redundancy. These methods provide an estimator of the fault frequency and an indicator of the quality of that estimation. These indicators are used to assess the severity of the fault. The four methods are then tested on synthesized and flight data in order to illustrate and discuss their efficiency.