Output-Only Modal Analysis for System Identification before Break Squeal

2018-01-1503

06/13/2018

Event
10th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference
Authors Abstract
Content
Typically, squealing brakes are identified at squealing conditions for FE model validation by an operational deflection shape analysis (ODS). The deflection shapes and the squealing frequency depend strongly on various internal and external boundary conditions.
If the model requires more modal information about the brake system than the ODS delivers an additional experimental modal analysis (EMA) can be conducted at standstill. In total, both analyses - ODS and EMA - cover only two distinctive operation points of the brake and do not provide further information. Plus, both are special cases since the usual brake condition should be a quiet braking process.
To validate the internal and external boundary conditions of the brake system it is useful to have more operation points for model alignment. Because it is difficult to measure the excitation during such a quiet braking action only an operational modal analysis (OMA) can be used to identify the brake system at any arbitrary brake condition.
In this paper, the method of OMA is transmitted from civil structures which are typically vibrating at frequencies below 5 Hz to hydraulic brake systems which squeal with 1-10 kHz. This involves several difficulties for the algorithm to be used as well as challenges for the measuring equipment due to the required analyzer settings.
In the end, one particular OMA algorithm is chosen from several possibilities in frequency and time domain and is presented together with the associated identification results for one exemplary brake system.
Meta TagsDetails
DOI
https://doi.org/10.4271/2018-01-1503
Pages
6
Citation
Siegl, B., and Bauer, J., "Output-Only Modal Analysis for System Identification before Break Squeal," SAE Technical Paper 2018-01-1503, 2018, https://doi.org/10.4271/2018-01-1503.
Additional Details
Publisher
Published
Jun 13, 2018
Product Code
2018-01-1503
Content Type
Technical Paper
Language
English