Brief paper: Bayesian approaches for identification of the complex modulus of viscoelastic materials

Authors:
Kaushik Mahata;Torsten Söderström
Affiliations:
Centre for Complex Dynamic Systems and Control, School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, NSW 2308, Australia;Department of Information Technology, Division of Systems and Control, Uppsala University, P.O. Box 337, SE-75105 Uppsala, Sweden
Venue:
Automatica (Journal of IFAC)
Year:
2007

Citing 3
Cited 0

Discrete-time signal processing (2nd ed.)

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Non-parametric identification of viscoelastic materials from wave propagation experiments

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Computationally efficient estimation of wave propagation functions from 1-D wave experiments on viscoelastic materials

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Abstract

Frequency domain identification of the complex Young's modulus of a viscoelastic solid from wave propagation experiment data is considered in this paper. The conventional techniques use a non-parametric approach, where the estimate at a particular frequency is independent of the estimate at another frequency. Here we show that the estimation accuracy can be improved significantly by taking the continuity of the complex modulus into account. In particular, we propose Bayesian estimation approaches to impose the continuity property. The estimation algorithms are computationally efficient. The analytical claims are also substantiated in experimental studies.