GEAR AND BEARING FAULT DETECTION USING WAVELET PACKET AND HILBERT METHOD VIA ACOUSTIC SIGNALS

Abstract

Detection of gearing and bearing faults using vibration signals has been widely used for decades. A lot of methods of vibration signal processing for fault detection have been used, such as fast Fourier transform, Hilbert transform, wavelet and wavelet packet transform. In recent years, a new method for vibration signal processing, combining Hilbert transform and wavelet packet appeared, and has become an effective method to extract modulating signal and help to detect the early gearing and bearing faults. The article deals with the use of the combination of wavelet packet method and Hilbert transform for processing acoustic signals to identify bearing and gearing faults in a two-stage gearbox test rig. Three simultaneous faults are made: a chipped tooth on the input pinion, a pitting tooth on the output gear and a pitting (spall) on the outer race of a rolling bearing on output shaft. By comparison of the processed acoustic signals of normal and faulty gearbox, these three faults can be exactly detected.