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.

摩擦学行为的特点是其响应具有很强的非线性效应，这是标准信号处理方法难以识别的。磨损现象分析的挑战之一是识别其传播和潜在的量化。在我们的研究中，我们建议应用基于小波的方法，即连续小波变换和尺度指数来分析摩擦对中的动态响应。分析的参数将是摩擦系数，它随着摩擦副的磨损而略有变化。执行的分析显示了系统在每个考虑状态下的可变响应。此外，用小波获得的结果可用于其确定。所提出的方法在运输应用中特别有用，其中滑动对应物之间摩擦力的量化是一个关键参数，负责功率损失。早期和有效的磨损识别允许预测损坏并避免不希望的停机时间或磨损零件的耗时更换。