Revealing transitions in friction-excited vibrations by nonlinear time-series analysis

Publisher:
Springer Science and Business Media LLC
Publication Type:
Journal Article
Citation:
Nonlinear Dynamics, 2019, 98, (4), pp. 2613-2630
Issue Date:
2019-12-01
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© 2019, Springer Nature B.V. We study the transitions in friction-induced vibrations (FIV) experimentally. The measurement data stem from a highly sophisticated setup specifically designed to study FIV problems and where the relative motion between the samples is achieved using air bearings and a voice-coil motor. This peculiarity ensures avoiding parasitic vibrations and makes the setup particularly suitable to perform measurements of very low vibration levels. The relative sliding velocity decays along the measurement to zero, which provokes several types of FIV. We employ advanced time-series analysis techniques, such as spectral analysis, attractor reconstruction and recurrence plot analysis to study the dynamical transition from steady sliding to high-frequency FIV and stick-slip vibrations in detail. For different specimens, self-excited vibrations are observed stemming from an instability that is driven by a negative friction-velocity slope characteristic as well as for constant friction values. Prior to instability, it is observed that highly irregular oscillations decay and most of the vibration energy focuses in a low-frequency mode of the experimental setup. The analysis of the FIV range illustrates a plethora of qualitatively different dynamics that can be detected, characterized and visualized using advanced signal processing. Particularly, we report on period-1 and period-2 limit cycles, quasi-periodic motion, weakly chaotic attractors and different types of stick-slip vibrations. The analysis of transitions between those dynamic regimes reveals beating phenomena, sudden energy exchange between different modes and intermittent dynamics. The results of this study aim to provide a step forward on the application of nonlinear dynamics post-processing tools for identifying and characterizing the different frictional stable and unstable scenarios.
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