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

• 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 x and the raw measurements d. 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
• Download:

  IMEKO-WC-2012-TC21-O21.pdf
• DOI:

  _unreg_wc-2012.TC21-O21

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