LAUSR

Tribological behaviour is characterized by the strong nonlinear effects in its response, which are hardly identified with standard signal processing methods. One of the challenges in the analysis of wear phenomena is identification of its propagation and potential quantification. In our study, we propose application of wavelet-based methods, i.e. continuous wavelet transform and scale index for analysis of the dynamical response in the tribological pair. The analysed parameter will be the coefficient of friction, which is slightly changing with wear of the tribological pair. The performed analysis shows the variable response of the system in each considered state. Moreover, results obtained with wavelets are useful for its determination. The proposed methods can be particularly useful in the transportation applications, where the quantification of the friction force between the sliding counterparts is a crucial parameter, responsible for the power losses. Early and efficient identification of wear allows to predict damage and avoid undesirable downtime or time-consuming exchange of a worn out part.