Condition Monitoring of Gears and Advanced Signal Processing Techniques towards More Effective Diagnostic Schemes

Abstract

A diagnostic methodology of artificial defects in a single stage gearbox operating under various load levels and different defect states is proposed in the present work based on vibration recordings as well as advanced signal analysis techniques. Two different wavelet-based signal processing methodologies, using the discrete as well as the continuous wavelet transform, were utilised for the analysis of the recorded vibration signals and useful diagnostic information were extracted out of them. Both wavelet analysis techniques provided the ability of distinguishing between the healthy and the artificially defected gears. In this way, the health monitoring potential of vibration monitoring in the case of rotating machinery and gearboxes obtains a new dynamic under the prism of sophisticated time-frequency signal processing schemes, rather than conventional FFT-based approaches.