2009
DOI: 10.1016/j.jsv.2008.05.034
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Sensitivity of friction-induced vibration in idealised systems

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Cited by 44 publications
(24 citation statements)
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“…Modelling of such a complex system and correlating the computed results to the measurements then becomes a challenging task. There is no validated predictive model of friction induced vibration to date [126]. It has been suggested that a brake system is highly sensitive to uncertainties [127].…”
Section: Hammeringmentioning
confidence: 99%
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“…Modelling of such a complex system and correlating the computed results to the measurements then becomes a challenging task. There is no validated predictive model of friction induced vibration to date [126]. It has been suggested that a brake system is highly sensitive to uncertainties [127].…”
Section: Hammeringmentioning
confidence: 99%
“…The study of sensitivity in disc-pad systems is now attracting the attention of research community (see e.g. [128,129,126,130,127]). In [131], to take the uncertainties into account, descriptive statistical analysis tools were used.…”
Section: Hammeringmentioning
confidence: 99%
“…Brake noise is a largely elusive phenomenon, partly due to the stochastic features of friction and the relevant timevarying factors such as interface profile, wear, interface films. The theoretical stochastic models have been developed to address variability and uncertainty in brakes noise [25][26][27][28][29][30][31][32][33][34]. A typical study is reported in [26], which documented a robust design of a disc brake through structural optimization using the complex eigenvalue approach, considering the variation of friction coefficient, major elastic constants and the effect of material worn-off.…”
Section: Historic Perspectives: the Example Of Brake Noisementioning
confidence: 99%
“…The system will be unstable if and only if all the zeros of both E 1 (ω) and E 2 (ω) lie in the upper half-plane (Butlin and Woodhouse, 2009). …”
Section: Dynamic Modellingmentioning
confidence: 99%
“…However, the question of their accuracy for approximating more complicated systems is often left untested. A study of very low-order models has demonstrated that predictions can be highly sensitive to system parameters under sometimes surprising conditions (Butlin and Woodhouse, 2009). Related to this issue is the sensitivity of predictions to changes in the complexity of the model, rather than just parameter values.…”
Section: Low-order Models Sensitivity and Convergencementioning
confidence: 99%