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Sequential Monte Carlo Methods for Electromagnetic NDE Inverse Problems—Evaluation and Comparison of Measurement Models

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2 Author(s)
Khan, T. ; Dept. of Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI ; Ramuhalli, P.

Flaw profile estimation from measurements is a typical inverse problem in electromagnetic nondestructive evaluation (NDE). The application of recursive Bayesian nonlinear filters based on sequential Monte Carlo methods, in conjunction with measurement process models and a Markovian crack growth model, is a new approach for solving such inverse problems. The approach resembles the classical discrete-time tracking problem and is robust to the noisy measurement data. This paper reports a comparative study of the results of employing different measurement models in this Bayesian inversion framework. The results are evaluated on the basis of accuracy and computational cost.

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Magnetics, IEEE Transactions on  (Volume:45 ,  Issue: 3 )