Determining growth rates of instabilities from time-series vibration data: Methods and applications for brake squeal

Stender, M; Tiedemann, M; Hoffmann, L; Hoffmann, N

Determining growth rates of instabilities from time-series vibration data: Methods and applications for brake squeal

Stender, M

Tiedemann, M Hoffmann, L Hoffmann, N

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Publication Type:: Journal Article
Citation:: Mechanical Systems and Signal Processing, 2019, 129 pp. 250 - 264
Issue Date:: 2019-08-15

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Field	Value	Language
dc.contributor.author	Stender, M https://orcid.org/0000-0002-0888-8206	en_US
dc.contributor.author	Tiedemann, M	en_US
dc.contributor.author	Hoffmann, L	en_US
dc.contributor.author	Hoffmann, N	en_US
dc.date.issued	2019-08-15	en_US
dc.identifier.citation	Mechanical Systems and Signal Processing, 2019, 129 pp. 250 - 264	en_US
dc.identifier.issn	0888-3270	en_US
dc.identifier.uri	http://hdl.handle.net/10453/138394
dc.description.abstract	© 2019 Elsevier Ltd In this work, a novel and generic methodology to derive instability growth rates from vibration time-series data is introduced. Spectral filtering using Fourier and wavelet transforms is employed to obtain the amplitude evolution of the major vibration frequency from the raw vibration signal. Then, the transient phase, i.e. the temporal regime in which the vibrations grow rapidly, is found and extracted. An exponential fit is applied to the amplitude series to estimate the local instability growth rate. A statistical framework is introduced by variation of the fitting regime and definition of fitting errors in order to obtain a robust growth rate estimate from a multitude of fits. Using this methodology, growth rates are extracted from time-series vibration signals for a large set of laboratory data from commercial passenger car testing for the first time. Specifically, self-excited brake system vibrations, commonly known as brake squeal, are studied in this research. Two different brake systems exhibiting various squeal instabilities are analyzed. Results show that the proposed approach is robust and applicable in a highly automated fashion to large data sets. The data analysis reveals that the final acoustical squeal intensity develops independently of the instability growth rates. Loading conditions which lead to squeal are extracted from the testing data. These loading conditions are then studied to illustrate growth rate dependencies on operational parameters and link results to the existing understanding of bifurcations and nonlinear dynamics in self-excited friction brake systems.	en_US
dc.relation.ispartof	Mechanical Systems and Signal Processing	en_US
dc.relation.isbasedon	10.1016/j.ymssp.2019.04.009	en_US
dc.subject.classification	Acoustics	en_US
dc.title	Determining growth rates of instabilities from time-series vibration data: Methods and applications for brake squeal	en_US
dc.type	Journal Article
utslib.citation.volume	129	en_US
utslib.for	0913 Mechanical Engineering	en_US
utslib.for	0905 Civil Engineering	en_US
utslib.for	0915 Interdisciplinary Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	129	en_US

Abstract:

© 2019 Elsevier Ltd In this work, a novel and generic methodology to derive instability growth rates from vibration time-series data is introduced. Spectral filtering using Fourier and wavelet transforms is employed to obtain the amplitude evolution of the major vibration frequency from the raw vibration signal. Then, the transient phase, i.e. the temporal regime in which the vibrations grow rapidly, is found and extracted. An exponential fit is applied to the amplitude series to estimate the local instability growth rate. A statistical framework is introduced by variation of the fitting regime and definition of fitting errors in order to obtain a robust growth rate estimate from a multitude of fits. Using this methodology, growth rates are extracted from time-series vibration signals for a large set of laboratory data from commercial passenger car testing for the first time. Specifically, self-excited brake system vibrations, commonly known as brake squeal, are studied in this research. Two different brake systems exhibiting various squeal instabilities are analyzed. Results show that the proposed approach is robust and applicable in a highly automated fashion to large data sets. The data analysis reveals that the final acoustical squeal intensity develops independently of the instability growth rates. Loading conditions which lead to squeal are extracted from the testing data. These loading conditions are then studied to illustrate growth rate dependencies on operational parameters and link results to the existing understanding of bifurcations and nonlinear dynamics in self-excited friction brake systems.

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http://hdl.handle.net/10453/138394