FAST ESTIMATION AND UNCERTAINTY QUANTIFICATION IN ELECTRICAL CAPACITANCE TOMOGRAPHY USING SURROGATE TECHNIQUES

M. Neumayer, D. Watzenig, G. Steiner

Abstract

The need for uncertainty quantification (UQ) in metrology has seen serious research efforts and is of ever-growing interest in order to quantify the quality of measurement results. This especially holds for indirect measurement problems. Bayesian methods allow a natural and universal access for UQ but become computationally expensive for scenarios with a complex interaction between the unknown quantity <i>x</i> and the raw measurements <i>d</i>. In this paper we present a surrogate approach for fast estimation and UQ of material distributions in the inverse problem of electrical capacitance tomography using a recursive Bayesian estimator.

Keywords

uncertainty quantification, electrical capacitance tomography, surrogate model, recursive Bayesian methods

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IMEKO-WC-2012-TC21-O21.pdf

DOI

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IMEKO TC

TC21 - Mathematical Tools for Measurements

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