System identification of an enclosure with leakages using a probabilistic approach

Lam, H. F., Ng, C. T., Lee, Y. Y. and Sun, H. Y (2009) System identification of an enclosure with leakages using a probabilistic approach. Journal of Sound and Vibration, 322 4-5: 756-771. doi:10.1016/j.jsv.2008.11.013

Author Lam, H. F.
Ng, C. T.
Lee, Y. Y.
Sun, H. Y
Title System identification of an enclosure with leakages using a probabilistic approach
Journal name Journal of Sound and Vibration   Check publisher's open access policy
ISSN 0022-460X
Publication date 2009-05-22
Year available 2008
Sub-type Article (original research)
DOI 10.1016/j.jsv.2008.11.013
Open Access Status
Volume 322
Issue 4-5
Start page 756
End page 771
Total pages 16
Place of publication United Kingdom
Publisher Elsevier Ltd
Language eng
Subject C1
Abstract This paper presents a model-based method for the system identification of a rectangular enclosure with an unknown number of air leakages subjected to uniform external noise, according to the probabilistic approach. The method aims to identify the number and corresponding locations and sizes of air leakages utilizing a set of measured, interior, sound pressure data in the frequency domain. System identification of an enclosure with an unknown number of air leakages is not trivial. Different classes of acoustic models are required to simulate an enclosure with different numbers of leakages. By following the traditional system of identification techniques, the “optimal” class of models is selected by minimizing the discrepancy between the measured and modeled interior sound pressure. By doing this, the most complicated model class (that is, the one with the highest number of uncertain parameters) will always be selected. Therefore, the traditional system identification techniques found in the literature to date cannot be employed to solve this problem. Our proposed system identification methodology relies on the Bayesian information criterion (BIC) to identify accurately the number of leakages in an enclosure. Unlike all deterministic system identification approaches, the proposed methodology aims to calculate the posterior (updated) probability density function (PDF) of leakage locations and sizes. Therefore, the uncertainties introduced by measurement noise and modeling error can be explicitly addressed. The coefficient of variable (COV) of uncertain parameters, which can be easily calculated from the PDF, provides valuable information about the reliability of the identification results.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

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Created: Sat, 06 Jun 2009, 01:58:42 EST by Siona Saplos on behalf of Office of Sponsored Research