A COMPARATIVE STUDY OF ACOUSTIC AND VIBRATION SIGNALS IN DETECTION OF GEAR FAILURES USING WIGNER_VILLE DISTRIBUTION

Vibration analysis is widely used in machinery diagnostics and the Wigner_Ville distribution has also been implemented in many applications in the condition monitoring of machinery. In contrast to previous applications, this paper examines whether acoustic signal can be used effectively to detect the various local faults in gearboxes using the smoothed pseudo-Wigner_Ville distribution. Three types of progressing local faults, broken tooth, gear crack and localised wear, were simulated. The results from acoustic signals were compared with vibration signals. The results suggest that acoustic signals are very affective for the early detection of faults and may provide a powerful tool to indicate the various types of progressing faults in gearboxes.