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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 88
PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY
Edited by: B.H.V. Topping and M. Papadrakakis
Paper 116

Inverse Problem Sensitivity to System Uncertainties for Damage Detection in Piezoelectrics

G. Rus1, R. Palma1, R. Gallego1 and J.L. Pérez-Aparicio2

1Structural Mechanics & Hydraulic Engineering, University of Granada, Spain
2Structural and Continuum Mechanics, Polytechnic University of Valencia, Spain

Full Bibliographic Reference for this paper
, "Inverse Problem Sensitivity to System Uncertainties for Damage Detection in Piezoelectrics", in B.H.V. Topping, M. Papadrakakis, (Editors), "Proceedings of the Ninth International Conference on Computational Structures Technology", Civil-Comp Press, Stirlingshire, UK, Paper 116, 2008. doi:10.4203/ccp.88.116
Keywords: uncertainty analysis, sensitivity analysis, piezoelectric, finite element method, inverse problem, Monte Carlo analysis.

Summary
Piezoelectric ceramics are brittle and susceptible to fracture. Studies concerning the location of defects and the behaviour of the ceramics in presence of defects are required. The aim of this work is to solve the identification inverse problem of locating a defect inside a finite piezoelectric plate, using a model-based non-destructive evaluation procedure. To produce accurate inverse problem solutions, the optimal configuration excitation-measurement and the experimental and random errors should be studied and controlled.

The present study has two objectives: (i) to simulate realistic experimental noise; and ii) to find which variables increase the experimental noise and, therefore, deteriorate the inverse problem solution. For the first goal, an uncertainty analysis is performed using a Monte Carlo analysis, where the model is simulated by the finite element method. For the second goal, two new ways are explored: the first way consists in solving the inverse problem for various experimental noises studying their effect on the inverse problem results; for the second way, a sensitivity analysis is performed and the relation between the uncertainties in the measures and in the independent variables (material properties) are obtained.

The optimal configuration enables the accurate characterization of the damage for realistic noise and material property uncertainty levels.

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