Forward and inverse analysis for non-destructive testing based on electromagnetic computation methods

Abstract

EM computation methods for the simulation and reconstruction of the metallic plate properties are investigated in this thesis. Two major computational problems exist in EM NDT: the forward problem and the inverse problem. The forward problem is to calculate the frequency-dependent inductance for steel plates with arbitrary values of permeability, conductivity, thickness and lift-off (i.e. the distance between the sensor and test sample). The inverse problem involves how to determine each parameter, i.e. permeability, conductivity, thickness and lift-off from the frequency-dependent inductance measurements. The purpose of this dissertation is to develop advanced forward and inverse solvers. This work will mainly deal with metallic plate structure in the low-frequency induction scheme. For the forward problem, both edge-element FEM and Dodd and Deeds analytical solution to simulate the eddy current probe-coil problems are developed. The feasibility and accuracy of the proposed forward solvers are verified by experiments and numerical solutions. An example of computation of eddy currents in metallic plates is also carried out to test the performance of the solver. The dissertation then goes further to consider the solution of the inverse problem of determining unique values for the four variables - permeability, conductivity, thickness and lift-off (i.e. the distance between the sensor and test sample) from the multi-frequency inductance spectra. In particular, novel methods on how to compensate lift-off variations are proposed. In addition, CIP is explored to measure the permeability of ferrous plates. These methods are verified by measurement results from EM sensors. University: The University of Manchester Degree: Doctor of Philosophy (PhD) Candidate’s name: Mingyang Lu Date: February 2018 Thesis title: Forward and inverse analysis for non-destructive testing based on electromagnetic computation methods

Date of Award	1 Aug 2018
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Anthony Peyton (Supervisor) & Wuliang Yin (Supervisor)