Shejuan Xie

Efficient Numerical Solver for Simulation of Pulsed Eddy-Current Testing Signals

The pulsed eddy-current testing (PECT) method has the promising capabilities for detecting defects and evaluating material properties. It achieves this through its rich variety of frequency components and large driving electric current. Efficient numerical simulation of PECT signals plays an important role in probe optimization and quantitative signal processing. This study primarily focuses on the development of an efficient numerical solver for PECT signals, and its validation via the consideration of the nondestructive testing problems of wall thinning defects in pipes of nuclear power plants. A frequency domain summation method combined with an interpolation strategy was proposed and implemented. It is based on the finite element method with edge elements. The number of total frequencies used in signal summation and the number of selected frequencies for interpolation were thoroughly discussed. In addition, a code using the time domain integration method was also developed for the signal prediction of a transient PECT problem. It was used for comparison with the frequency domain summation method. A comparison of numerical results of the two proposed simulation methods and experimental results indicates that both of these simulation methods can model PECT signals with high precision. However, the frequency domain summation method combined with an interpolation strategy is much more efficient in its use of simulation time.

Sizing of Wall Thinning Defects Using Pulsed Eddy Current Testing Signals Based on a Hybrid Inverse Analysis Method

Quantitative non-destructive evaluation, especially sizing of piping wall thinning in nuclear power plants is still a difficult and urgent issue. In this paper, an inversion approach for PECT (pulsed eddy current testing) signals is developed based on ANN (artificial neural network) method at first for profile reconstruction of wall thinning, the sizing result of NN is then utilized as the initial value of the CG (conjugate gradient) inversion scheme to overcome the shortages of both the NN (accuracy problem) and CG (local minimum problem) methods. Several reconstruction examples using the proposed hybrid strategy indicate that the combination of NN and CG methods is rather effective for wall thinning reconstruction from PECT signals in view of both the robustness and sizing accuracy.

Quantitative Non-Destructive Testing of Metallic Foam Based on Direct Current Potential Drop Method

To detect cavity defects in metallic foam and to predict its size, a quantitative nondestructive testing (NDT) method based on the direct current potential drop (DCPD) technique was proposed and validated in this study. At first, an efficient forward analysis scheme was introduced to simulate the DCPD signals. In order to obtain measured signals for defect reconstruction, specimens of practical aluminum metal foam with defects of different sizes were fabricated and inspected then by using a DCPD testing system. Third, an inverse analysis scheme in model based optimization category was proposed and implemented for sizing cavity defects in the metal foam. Through inversion of both simulated and measured DCPD signals, the validity of both the forward and the inverse analysis schemes was demonstrated for the quantitative DCPD evaluation of the metallic foam.

Development of a novel fast solver for the direct current potential drop method and its verification with nondestructive testing of metallic foam

A fast forward scheme based on the Finite Element Method (FEM) and databases is proposed and developed for the rapid computation of Direct Current Potential Drop (DCPD) signals under condition of 3D FEM analysis for Nondestructive Testing (NDT) of Metallic Foam to reduce computer burden. Comparison of numerical results of the present method with those of full FEM code and experimental results of metallic foam indicates that the proposed novel fast forward scheme can predict DCPD signals accurately and over 100 times faster.

Reconstruction of Stress Corrosion Cracks Based on Pulsed Eddy Current Signals

Reconstruction of Stress Corrosion Cracks (SCCs) using conventional Eddy Current Testing method (ECT) shows its limitation especially when dealing with deep SCCs. Recently, a new approach utilizing Pulsed Eddy Current Testing (PECT) signals has been proposed to reconstruct wall thinning defect based on a deterministic optimization method. It is because PECT is found advantageous over the conventional ECT due to its features of abundant frequency components and large exciting currents. In this study, stochastic optimization methods of neural network, tabu search, simulated annealing and genetic algorithm are introduced to reconstruct the SCC profile from the PECT signals. The efficiency and accuracy of these stochastic methods are evaluated and discussed.

Sizing of metallic foam bubble flaws using direct current potential drop signals with the help of the neural network method

To investigate the possibility of reconstructing the position and size of bubble flaws in metallic foam, a Neural Network approach is applied to predict the flaw profile from Direct Current Potential Drop (DCPD) signals. A feed-forward network, improved by Principal Component Analysis (PCA) is selected for the inverse analysis. Over 100 sets of DCPD signals due to flaws with different positions and sizes are calculated using a newly developed fast forward solver and are used for the inverse analysis. Satisfactory reconstruction results are obtained for these simulated signals.

Evaluation of plastic deformation and characterization of electromagnetic properties using pulsed eddy current testing method

Plastic deformation, as a type of micro-damage caused by external loads such as earthquake, is necessary to be evaluated by using an efficient non-destructive evaluation technique in order to guarantee the structural safety. In this paper, the feasibility of the pulsed eddy current testing method for evaluating the plastic deformation in an austenitic stainless steel has been studied through experiments and simulations. Moreover, the electromagnetic property variations due toplastic deformation have also been investigated.

A study on influence of plastic deformation on the global conductivity and permeability of carbon steel

Non-destructive evaluation (NDE) techniques are indispensable for inspection of damage in structures of carbon steel, which is widely used in many industries. In this paper, experimental and numerical studies were conducted to investigate the electromagnetic property variations of carbon steel Q195 due to plastic strain by using the 4-probe potential drop method and ECT aiming at NDE applications. A series of specimens were fabricated and uniform global plastic strains of different levels were introduced to the specimens by tensile testing. 4-probe potential drop measurements were carried out to obtain the conductivity information at first. It is found that the macro conductivity is not affected significantly by the plastic strain once taking into account the influence of the cross-sectional area reduction of the specimens. Combining the results of numerical analysis using a code of Ar formulation with the measured ECT signals, the permeability of specimens with various plastic damages was evaluated through inverse analysis. It is proved that the ECT signal change due to plastic damages is mainly caused by the variation of permeability, which gives a good possibility to evaluate the plastic damage with a magnetic NDE method.

An Efficient Numerical Scheme for Sizing of Cavity Defect in Metallic Foam From Signals of DC Potential Drop Method

Quantitative nondestructive testing is important to guarantee the integrity of metallic foam (MF) structures. To predict the profile of a cavity defect in an MF material, a database-type fast forward scheme is upgraded at first by introducing a kind of multimedium element (MME) for the efficient simulation of dc potential drop (DCPD) signals of MF with defect of complicated shape. Second, a code of the hybrid strategy combining the neural network and the conjugate gradient optimization method is proposed to obtain the size and the position parameters of the defect. Both simulated and measured DCPD signals are adopted to reconstruct the bubble defects in MF. The good consistency of the true and the reconstructed results demonstrated the validity of the new scheme. In addition, it is also proved that the updated database-type fast-forward scheme is efficient for the signal simulation of MF with defect of complicated shape with the help of MME, and the hybrid inverse strategy has a better numerical performance for the defect sizing.

Reconstruction of stress corrosion cracks using signals of pulsed eddy current testing

A scheme to apply signals of pulsed eddy current testing (PECT) to reconstruct a deep stress corrosion crack (SCC) is proposed on the basis of a multi-layer and multi-frequency reconstruction strategy. First, a numerical method is introduced to extract conventional eddy current testing (ECT) signals of different frequencies from the PECT responses at different scanning points, which are necessary for multi-frequency ECT inversion. Second, the conventional fast forward solver for ECT signal simulation is upgraded to calculate the single-frequency pickup signal of a magnetic field by introducing a strategy that employs a tiny search coil. Using the multiple-frequency ECT signals and the upgraded fast signal simulator, we reconstructed the shape profiles and conductivity of an SCC at different depths layer-by-layer with a hybrid inversion scheme of the conjugate gradient and particle swarm optimisation. Several modelled SCCs of rectangular or stepwise shape in an SUS304 plate are reconstructed from simulated PECT signals with artificial noise. The reconstruction results show better precision in crack depth than the conventional ECT inversion method, which demonstrates the validity and efficiency of the proposed PECT inversion scheme.