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Imperialist Competitive Algorithm and Particle Swarm Optimization Comparison for Eddy Current Non-destructive Evaluation

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Imperialist competitive algorithm (ICA) and particle swarm optimization (PSO) are two approaches for determining the solution of any objective function, but they use different strategies. Therefore, a comparison of their performance is required. The comparison is made on the basis of test functions, and then both techniques are applied to an eddy current non-destructive evaluation system to reconstruct from an impedance measurement. An axisymmetric groove shape of a conductive tube is inspected by a differential probe. Streszczenie. W artykule przedstawiono wykorzystanie algorytmów ICA i PSO w systemie defektoskopii prądów wirowych. Jako model badań zastosowano rurę z materiału przewodzącego o rowkowym kształcie. (Wykorzystanie algorytmów ICA i PSO w defektoskopii prądów wirowych) Keywords: Imperialist competitive algorithm, particle swarm optimization, eddy current non-destructive evaluation, inverse problems. Słowa kluczowe: algorytm ICA - imperialist competitive algorithm, algorytm PSO - particle swarm optimization.. Introduction Eddy current non-destructive evaluation (NDE) is a method based on the fact that when a coil powered by a variable energy source is brought near a conductive part, a change in impedance at the terminals of the coil is driven by the changing of magnetic field lines due to the existence and the distribution of induced currents in the conductive part. The signal information representing the change in impedance of the coil is used for the evaluation of physical and geometrical characteristics of the latter. The geometric profile evaluation remains a major challenge because of complex shapes it takes in reality. The evaluation in eddy current non-destructive method is considered as an inverse problem that has been intensively studied in recent years [1-5]. Thus, the problem of forms reconstruction is formulated as an optimization problem to search for all geometrical parameters, and iteratively minimizing [...]

Eddy Currents Non Destructive Testing and Evaluation of Ferromagnetic Medium DOI:10.15199/48.2019.02.26

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There is nowadays an increasing attention and request towards the study and development of systems and techniques for increasing the human safety and security in all aspects of the everyday life. In this framework, the possibility to perform a non-invasive inspection of structures or objects by means of non-destructive testing and evaluation (NDT-NDE) technologies is of particular interests in several applicative fields, ranging from civil engineering to biomedicine, up to aeronautic and nuclear industries [1]. In non-destructive test methods, eddy current technology increasingly gains in importance. The reason for this is that it is a test method that is flexible in its application and that its probes, usually coils of copper wire, are very adaptable and can be produced fairly easily [2]. Eddy current non-destructive evaluation (NDE) is a method based on the fact that when a coil powered by a variable energy source is brought near a conductive part, a change in impedance at the terminals of the coil is driven by the changing of magnetic field lines due to the existence and the distribution of induced currents in the conductive part [3]. Besides the inspection of metallic samples for which ECT has been applied for some decades to detect cracks, voids, corrosion and other defect typologies structures [4, 5], this technique can also be used to distinguish between ferromagnetic and non-ferromagnetic materials. However, this technique does not allow access to accurate information that can characterize a defect in any form; this is why it is essential to dispose for a rapid tool for signal inversion as eddy current. For this, we are interested in an artificial neural networks. This technique is capable of solving complex problems using an artificial reasoning system constructed with basis on the human brain [6]. A calculation tool developed under Matlab environment was used. Simulation of direct problem with FEM The relevant c[...]

Inspection and characterization of random physical property defects by stochastic finite element method DOI:10.15199/48.2019.08.23

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Non-destructive techniques are used widely in the industry and science in order to control and evaluate the quality of materials without causing damage [1]. The most commonly used NDT methods are ultrasonic testing (UT), radiography (RT) and eddy current testing [2] . Eddy Current Testing (ECT) is the standard and one of the most extensively used nondestructive technique method of electric conductivity and magnetic permeability related property in conductive materials in order to evaluate them [1,3]. Whose main applications are found especially in the inspection of aircraft and nuclear industries [4,5], power plants and other engineering constructions [6]. Eddy Current sensors can be made to operate in differential [7] and absolute mode [8]. ECT gain interest in of simple, fast and noncontact testing [9]. Stochastic Finite Element Method SFEM is an extension of the classical deterministic approach for the solution of stochastic problems. It has received considerable attention, due to the rapid development of computer simulation, mathematical modeling and scientific computing to predict and understand the behavior of physical engineering and electromagnetic devices [10,11,12]. The Monte Carlo method is powerful, popular and easy to understand and implement, it is often used in the literature as a reference method in order to check the accuracy of other approaches. It has a large field applications such as analyzing complex problems, development of new material, industrial engineering, simulation of physical process and analysis of nonlinear inverse problems [10,13,14]. Various parameters induce change to the properties of the materials over time which is still in operation, not defective. It’s why in this work we assume the defect as a lack of material, corrosion, imperfections of fabrication process or aging. To take in account the effect of random physical properties in defects areas by coupling Monte Carlo method[...]

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