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

Stender, Merten; Bartolomeo, M. Di; Massi, Francesco; Hoffmann, Norbert

doi:10.1007/s11071-019-04987-7

Cited by 23 publications

(11 citation statements)

References 40 publications

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“…Motions in horizontal and vertical directions are viscously damped and coupled through the inclined stiffness k. The speed of the conveyor belt is assumed to always be larger than the horizontal velocity of the slider such that the system is not undergoing any stick-slip type dynamics and can be taken as linear. This assumption for high relative sliding velocities is supported by a recent experimental study [4]. A Coulomb-type friction force creates the asymmetrical circulatory terms N = −N that allow the system to flutter [9].…”

Section: Introductionmentioning

confidence: 75%

“…Energy harvesting from high-amplitude friction-induced vibrations (FIV) was proposed recently [3]. Even though friction-excited systems are well known to exhibit rich periodic and chaotic dynamic behavior [4], most systems show high vibration energy shares in narrow frequency ranges. Hence, energy harvesting resonators can be tuned accordingly and help to overcome the limitations of suboptimal frequency range coverage.…”

Section: Introductionmentioning

confidence: 99%

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Energy harvesting below the onset of flutter

Stender

Tiedemann

Hoffmann

2019

Journal of Sound and Vibration

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This work demonstrates preliminary results on energy harvesting from a linearly stable fluttertype system with circulatory friction forces. Harmonic external forcing is applied to study the energy flow in the steady sliding configuration. In certain parameter ranges negative excitation work is observed where the external forcing allows to pull part of the friction energy out of the system and thus makes energy harvesting possible. Studies reveal that this behavior is largely independent of the flutter point and thus that it is primarily controlled by the excitation. Contrary to existing energy harvesting approaches for such systems, this approach uses external forcing in the linearly stable regime of the oscillator which allows to control vibrations and harvest energy on demand.

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Section: Introductionmentioning

confidence: 75%

Section: Introductionmentioning

confidence: 99%

Energy harvesting below the onset of flutter

Stender

Tiedemann

Hoffmann

2019

Journal of Sound and Vibration

Self Cite

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“…They also proposed an automated framework based on RQA to detect and monitor brake squealing. In a related study, Stender et al [77] showed how RQA could help to identify transitions between different types of friction-induced vibration such as chaotic and weakly chaotic epochs, limit cycles and intermittent stick-slip dynamics.…”

Section: Recurrence Plots In Engineering Researchmentioning

confidence: 99%

A Brief Introduction to Nonlinear Time Series Analysis and Recurrence Plots

Goswami

2019

Vibration

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Nonlinear time series analysis gained prominence from the late 1980s on, primarily because of its ability to characterize, analyze, and predict nontrivial features in data sets that stem from a wide range of fields such as finance, music, human physiology, cognitive science, astrophysics, climate, and engineering. More recently, recurrence plots, initially proposed as a visual tool for the analysis of complex systems, have proven to be a powerful framework to quantify and reveal nontrivial dynamical features in time series data. This tutorial review provides a brief introduction to the fundamentals of nonlinear time series analysis, before discussing in greater detail a few (out of the many existing) approaches of recurrence plot-based analysis of time series. In particular, it focusses on recurrence plot-based measures which characterize dynamical features such as determinism, synchronization, and regime changes. The concept of surrogate-based hypothesis testing, which is crucial to drawing any inference from data analyses, is also discussed. Finally, the presented recurrence plot approaches are applied to two climatic indices related to the equatorial and North Pacific regions, and their dynamical behavior and their interrelations are investigated.

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“…The friction coefficient decreased with the increasing vibration amplitude and converged to a specific value with the increasing rub cycle. To study the transient phenomenon, Stender et al [8] studied the difference of some kinds of vibration by friction.…”

Section: Introductionmentioning

confidence: 99%

The Feature Extraction through Wavelet Coefficients of Metal Friction Noise for Adhesive and Abrasive Wear Monitoring

et al. 2021

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Friction between metals is a physical phenomenon that occurs in manufacturing machine tools. This annoying noise implies unnecessary metal contact and deterioration of a mechanical system. In this study, for the monitoring of the friction between two metal surfaces, the acoustic signature was extracted by applying the wavelet transform method to the noise measured from the change in contact force for each state of adhesive and abrasive wear. Experiments were conducted with a constant relative speed between the contacting metal surfaces. For the adhesive wear, the peak signal-to-noise ratio (PSNR) calculated by the wavelet transformation increases with the increasing contact pressure. Opposite trends were observed for the abrasive wear. The proposed index formed a group within a specific range. This ratio exhibited a strong relationship with the wear characteristics and the surface condition. From the proposed index calculated by the wavelet coefficients, the continuous monitoring of the wear influence on the failure of the machine movement operations is achieved by the sound radiation from the contacting surfaces.

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

Cited by 23 publications

References 40 publications

Energy harvesting below the onset of flutter

Energy harvesting below the onset of flutter

A Brief Introduction to Nonlinear Time Series Analysis and Recurrence Plots

The Feature Extraction through Wavelet Coefficients of Metal Friction Noise for Adhesive and Abrasive Wear Monitoring

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