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Eddy current imaging is a relatively new technique of electromagnetic nondestructive testing that makes possible an accurate geometrical characterization of flaws. On contrary to the traditional approach to eddy current testing, spatially correlated information, that can be extracted from two‐dimensional eddy current images, is used to infer about flaw shape and dimensions. In general the problem of flaw reconstruction from the eddy current images belongs to the class of three‐dimensional nonlinear inverse problems. These problems can not be solved without properly chosen simplifications. In recent literature most of the authors tried to take advantage from the problem linearization. They used the eddy current image of a small diameter hole as a point spread function (two‐dimensional impulse response) and applied the classical linear filtering to deblur the image. Although this approach results in the restoration of the top view of the flaw it seems to be inadequate for full flaw reconstruction.

The inverse problem in the eddy current (EC) imaging of metallic parts is an ill‐posed problem. The purpose of the paper is to compare the performances of regularized algorithms to estimate the 3D geometry of a surface breaking defect.

The forward problem is solved using a mesh‐free semi‐analytical model, the distributed point source method, which allows EC data to be simulated according to the shape of the considered defect. The inverse problem is solved using two regularization methods, namely the Tikhonov (l2) and the 3D total variation (tv) methods, implemented with first‐ and second‐order algorithms. The inversion performances were evaluated in terms of both mean square error (MSE) and computation time, while considering additive white and colored noise, respectively, standing for acquisition errors and model errors.

In presence of colored noise, the authors found out that first‐ and second‐order methods provide approximately the same result according to the SEs obtained while estimating the defect voxels. Nevertheless, in comparison with (l2), the (tv) regularization was proved to decrease the MSE by 10 voxels, at the cost of less than twice the computational effort.

In this paper, an easy to implement mesh‐free model, based on virtual defect current sources, was used to generated EC data relative to a defect positioned at the surface of a metallic part. A 3D total variation regularization approach was used in combination with the proposed model, which appears to be well suited to the reconstruction of volumic defects.

Magnetic induction tomography (MIT) is a tomographic imaging technique with a wide range of potential industrial applications. Planar array MIT is a convenient setup but unable to access freely from the entire periphery as it only collects measurements from one surface, so it remains challenging given the limited data. This study aims to assess the use of sparse regularization methods for accurate position and depth detection in planar array MIT.

The most difficult challenges in MIT are to solve the inverse and forward problems. The inversion of planar MIT is severely ill-posed due to limited access data. Thus, this paper posed a total variation (TV) problem and solved it efficiently with the Split Bregman formulation to overcome this difficulty. Both isotropic and anisotropic TV formulations are compared to Tikhonov regularization with experimental MIT data.

The results show that Tikhonov method failed or underestimated the object position and depth. Both isotropic and anisotropic TV led to accurate recovery of depth and position.

There are numerous potential applications for planar array MIT where access to the materials under testing is restrict. Sparse regularization methods are a promising approach to improving depth detection for limited MIT data.

A data fusion approach to the classification of eddy current and ultrasonic measurements is proposed in a context of defect detection/recognition methods for non‐destructive testing/evaluation systems: the purpose is to demonstrate that a multi‐sensor approach that combines the advantages carried by each sensor is able to locate potential cracks on the inspected specimen. Different approaches have been compared: a pixel level data fusion approach, that distinguishes between the defect area and the no‐defect areas, by means of the information carried by the intensity of each pixel of the eddy current and ultrasonic data; a feature level data fusion approach that uses the features computed on the measured data; a symbol level data fusion approach that extracts symbols from the two sensors as complementary information and classifies the data by using these symbols. The experimental results, carried out on an aluminium plate, pointed out the ability of the symbol level proposed approach to classify the input images within a minimum overall error, by taking into account the probability of detection and the probability of false alarm for the defect.

Detection of hidden defects of aluminum alloy plate with damping coating is a challenging problem. At present, only a few non-destructive testing methods exist to address this engineering problem. Without the restriction of skin effect, remote field eddy current (RFEC) overcomes the interference caused by the damping coating. The RFEC, which has potential advantages for detecting the hidden defects of aluminum plate with damping coating, can penetrate the metal plate to detect buried depth defects. This study aims to test how thick the RFEC sensor can penetrate the metal plate to detect the buried defects.

The magnetic field distribution characteristics are analyzed, the magnetic field intensity distribution is calculated, and the structure and parameters of the coil, magnetic circuit and shielding damping are determined through the two- and three-dimensional finite element simulation methods. Optimal excitation frequency is obtained, and the distance between the excitation coil and detection coil is determined by analyzing the relationship between excitation frequency and remote field points.

Simulation and experimental results verify the feasibility of applying the RFEC detection technology in detecting the hidden defects of aluminum alloy plate with damping coating.

In this paper, the RFEC testing model of hidden defects in aluminum plate sample with damping coating is established by using the finite element method.

This paper aims to propose a new 3D electromagnetic model to compute translational motion eddy current in the conducting plate of a novel linear permanent magnet (PM) induction heater. The movement of the plate in a DC magnetic field created by a PM inductor generates induced currents that are at the origin of a heating power by Joule effect. These topologies have strong magnetic end effects. The analytical model developed in this work takes into account the finite length extremity effects of the conducting plate and the reaction field because of induced currents.

The developed model is based on the combination of the sub-domain’s method and the image’s theory. First, the magnetic field expressions because of the PMs are obtained by solving the three-dimensional Maxwell equations by the method of separation of variables, using a magnetic scalar potential formulation and a magnetic field strength formulation. Then, the motional eddy currents are computed using the Ampere law, and the finite length extremity effects of the conducting plate are taken into account using the image’s method. To analyze the accuracy of the proposed model, the obtained results are compared to those obtained from 3D finite element model (FEM) and from experimental tests performed on a prototype.

The results show that the developed analytical model is very accurate, even for geometries where the edge effects are very strong. It allows directly taking into account the finite length extremity effects (the transverse edge effects) of the conducting plate and the reaction field because of induced currents without the need of any correction factor. The proposed model also presents an important reduction in computation time compared to 3D finite element simulation, allowing fast analysis of linear PM induction heater.

The proposed electromagnetic analytical model can be used as a quick and accurate design tool for translational motion PM induction heater devices.

A new 3D analytical electromagnetic model, to find the induced power in the conducting plate of a novel translational motion induction heater has been developed. The studied heating device has a finite length and a finite width, which create edge effects that are not easily considered in calculation. The novelty of the presented method is the accurate 3D analytical model, which allows finding the real power heating and real distribution of the induced currents in the conducting plate without the need to use correction factor. The proposed model also takes into account the reaction field because of induced currents. In addition, the developed model improves an important reduction in the computation time compared with 3D FEM simulation.

Robust design is very important for manufacturers to ensure the quality of the finished product. Therefore, a robustness measure is needed for the topological design of electromagnetic problems which may be sensitive to parameter variations. The purpose of this paper is to propose a robust objective function for topological design problems.

In this paper, a robust objective function for topology optimization is defined on an uncertainty set using the worst case analysis. The robustness of a topological design is defined as the worst response due to the variations of the location of the topology change. The approach is based on the definition of a topological gradient.

The robust topology optimization (RTO) was applied to eddy current crack reconstruction problems. The numerical applications showed that this method can provide more reliable results for the reconstruction in the presence of significant noise in the measured signal.

The RTO may be applied to some more complicated design problems; however large computational costs may result.

This paper has defined a robustness metric for topology design and a robust design model is proposed for topology optimization problems.

The purpose of this paper is to develop a magnetic induction tomography (MIT) system as well as the conductivity reconstruction algorithms (inverse problem).

In order to define and verify the solution of the inverse problem, the forward problem is formulated using mathematical model of the system. The forward problem is solved using the finite element method. The optimization of the excitation unit is based on the numerical solutions of the direct problem. All the dimensions and shape of the excitation system are optimized in order to focus the main part of the magnetic field in the vicinity of the receiver. Finally, two formulations of the inverse problem are discussed: based on the inversion of the Biot‐Savart law; and based on the artificial neural networks.

The formulation of the forward problem of the considered MIT system is given. The construction of the exciter unit that focuses the main part of the magnetic field in the vicinity of the receiver is proposed. Two formulations of the inverse problem are discussed. First using the inversion of the Biot‐Savart law and second using the artificial neural network. The neural networks seem to be promising tools for reconstructing the MIT images.

This paper demonstrates a real‐life MIT system whose performance is satisfactorily predicted by mathematical models. The original design of the exciter is shown. The new approach to the inverse problem in MIT – the use of the artificial neural network – is presented.

Flexible eddy current array (FECA) sensor is flexible and light in weight, which has broad application prospects in structural health monitoring. But, the sensor’s sensing channel number is more, increasing the added mass of sensor networks. This paper aims to reduce the sensing channel number by changing the sensing coil layout.

In this paper, FECA sensors with series sensing coil (SSC) layout and interactive sensing coil (ISC) layout are proposed, which reduce the number of sensor’s channels by half. Then, the variation of the output signal of the sensor when the crack expands along both sides of the hole is analyzed by simulation model. Finally, the fatigue crack monitoring experiment is carried out.

For the SSC layout, the simulation results show that the amplitude of each SSC group of the sensor increases when the crack propagates to the left or right. For the ISC layout, when the crack propagates on the right side of bolt hole, the induced voltage of each ISC group decreases. When the crack propagates on the left side of bolt hole, the induced voltage of each ISC group increases. The experiment results are consistent with simulation results, which verifies the correctness of simulation model. Compared with SSC layout, the ISC layout can judge the crack propagation direction. And the crack monitoring accuracy is 1 mm.

The research results provide a certain reference for reducing the number of sensor’s sensing channels. Results of the simulation and experiment show that the ISC layout can judge the crack propagation direction, and the crack monitoring accuracy is 1 mm.

The paper aims to develop a robot that climbs on non‐ferrous surfaces, e.g. aircraft wings and fuselages, carrying a heavy payload up to 18 kg including scanning arm and various equipments, for non‐destructive testing (NDT).

This robot in the study uses vacuum suction cups for adhesion, and two pairs of pneumatic cylinders to drive itself, moving in two directions in stepping gait. A rotation mechanism in the centre is used to correct the off‐course deviations by ± 5 degrees. Multiple universal joints are used to make every single suction cup, every robot foot and the whole structure flexible to negotiate with varying surface curvatures presented in different parts of aircraft. This flexible structure is also rigid once the robot is stuck on the surface to enable the NDT inspection being carried out reliably.

The paper finds that the walking speed is limited by the cylinder stroke, time for generating vacuum and changing legs. Although most NDT inspection is time‐consumable, it is still desirable to increase the robot speed.

The application of this robotic NDT can significantly reduce the cost of aircraft inspection, eliminate labour‐intensive and monotonous inspection tasks and eliminate the need for an operator to work in confined and dangerous spaces.

The paper introduces the structure that combines flexibility and rigidity for a robot climbing on non‐ferrous curvatures.