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The eddy current method of non‐destructive testing uses an alternating current excitation to induce secondary currents in a specimen under test. Flaws within the specimen affect the induced currents, causing changes in the impedance of a test coil. In this paper we present a method for obtaining a solution of inverse problems, in which the parameters of defects are unknown and the excitation function and the eddy current system response are given. The method is based on the use of artificial neural networks, which are trained using measurements. Illustrative examples are given.

Development in microcomputer systems has led to their use for a three‐dimensional magnetic field calculation. It caused a great progress in numerical methods used for a magnetic field analysis in electric machines and devices. Determination of the calculations quality may be achieved by comparing with the measurements. For this purpose real objects or simplified models can be used.

The purpose of this paper is to present capabilities of terahertz imaging technology in case of various composite materials and to propose a new defect detection algorithm.

This paper first discusses an applicability of the terahertz technique in composite materials inspection. It then describes source of terahertz radiation (photoconductive antenna) and general structure of terahertz time domain imaging system. Next the terahertz imaging results of composite anticorrosion coating, glass‐ and carbon‐fiber‐reinforced laminates are presented. Then the signal processing and identification scheme based on time domain A‐scan signal equalization and C‐scan thresholding is presented. Data processed in this way are parameterized and defect identification database is prepared. The proposed procedure is verified using the exemplary inspection results of glass‐fiber laminate delamination. Finally, some comparison of terahertz time domain inspection with low energy digital radiography is presented.

This paper shows terahertz imaging as a well‐suited technique for composite structures inspection. The terahertz imaging results of composite anticorrosion coating, glass‐ and carbon‐fiber‐reinforced laminates are presented. An application of proposed signal processing algorithm enables accurate defects detection and effective data collection for identification database purpose.

The paper provides an insight into the potential of terahertz imaging of various composite structures. Proposed signal processing and defects detection scheme is applicable to wide range of composite structures.

This paper presents an efficient procedure for reconstructing the aged region of ferromagnetic material.

The aging of the ferromagnetic material leads to changes of B ‐H relationship. This property may be used for detection of the degraded parts of ferromagnetic pieces. In numerical procedures the region with a possible aged zone is described by a finite number of subdomains where the flaw vector is defined with binary entries.

Because of the small B ‐H changes, the magnetic field modifications linearly depend (matrix T) by the flaw vectors. Using a double Gauss pivotation scheme, an enough well conditioned and invertible submatrix is extracted from the matrix T. The unknowns associated with this submatrix (called main unknowns) can be easily obtained by a linear relationship from the rest of the unknowns (called minor). In the set of the minor unknowns we search for that vector which gives the smallest error of the principal unknowns in comparison with the values 0 or 1.

This procedure leads to a spectacular increasing of the efficiency in comparison with the known procedures.

The goal of the paper is to introduce a new method of obtaining equivalent dynamic model of electromagnetic field quantities. Proposed algorithm allows approximation of the frequency and step response by a simple inertial element model, with adjustable rank and delay. The values of the model parameters may be also used to describe the dynamics of considered system.

The dynamics of interesting field quantity in certain space location may be represented by an equivalent model of inertial element. Parameters of the model are identified using the solution of the problem in quasi‐stationary conditions for very limited number of excitation frequencies. These solutions are further used to build a matching approximation of real frequency response function (FRF).

The proposed method allows fast approximation of transient states of linear vector field. It may be useful with fast and relatively precise estimation of dynamic parameters of the electromagnetic field, e.g. in screening and eddy current problems.

The main limitation of the method is the assumption of linearity of the problem. However, many practical tasks similar to the examples presented in the paper can be considered highly linear.

The main advantage of the method is that it allows fast estimation of the field dynamics without either solving the problem for whole range of frequencies or computing the transient state in time domain. It does not need the access to the original mass and stiffness matrices. Therefore, it may be used with commercial FEM software, which usually restricts access to its internal data.

The method is based on well known concept of moments, but the use of existing stationary FEM solutions for approximating transient states is a novel approach. Proposed procedure may be easily automated for the simulation environments with scripting capabilities.

The purpose of this paper is to describe the full‐wave modelling of pulsed terahertz systems utilized in non‐destructive testing.

At the outset, some basic information on the terahertz NDT are outlined and then, general remarks on its numerical modelling are presented. Frequency domain FEM and time domain FDTD analysis is carried out. Finally comparison of computed and measured signals is shown in order to prove numerical analysis correctness.

It is possible to model in a relatively simple way a terahertz system for nondestructive evaluation of dielectric materials. In contrast to other published work, the entire measuring setup is modelled, including photoconductive antenna with hemispherical lens, focusing lens and evaluated material with exemplary defect.

This paper gives a description of the terahertz non‐destructive testing system with comparison of simulated and measured results.

In the paper a new probe for eddy current testing of low conductivity materials is presented. The new probe has been applied for eddy current testing of H₂SO₄ water solution. Results of measurements are presented.

The aim of the paper is to develop an algorithm based on fuzzy logic (FL) systems for reconstructing cracks shapes, which will be faster and simpler to learn than neural networks, especially in case of large training set.

The inverse model in defectoscopy can be considered as reverse model of the whole measurement process (crack‐sensor‐output). The most important disadvantage of the inverse neural models with dynamic networks is that the performance of training is disappointing due to large training set and many inputs of such networks. The paper proposes the FL as the substitute of neural network. The typical ANFIS networks are sufficient only for simulating systems with small number of inputs. For this reason the paper developed the learning algorithm that produces relatively small number of rules and it can be used in case of systems with hundred of inputs and thousands of training pairs.

This paper provides details about algorithm for reconstructing cracks profiles that produces relatively small number of rules of the fuzzy system. The basis rule of inverse model with moving window for one‐ and multi‐frequency method is described. The results of profile identification in 2D and 3D space for real and simulated data are presented as well.

Generally, the algorithm proposed in this paper can be widely used for simulating multi‐input systems, which are described by a large training set.

The purpose of this paper is to present a system for automatic recognition of defects detected in non-conductive polymer composites using pulsed terahertz imaging.

On the beginning, non-destructive evaluation of composites using electromagnetic waves in terahertz frequency is shortly introduced. Next automatic defects recognition (ADR) algorithm is proposed, focussing on new features calculation. Dimensionality of features space is reduced by using principal component analysis. Finally, results of basalt fiber reinforced composite materials inspection and identification using artificial neural networks is presented and discussed.

It is possible to develop ADR system for non-destructive evaluation of dielectric materials using pulsed terahertz technique. New set of features in time and frequency domains is proposed and verified.

ADR in non-destructive testing is utilized in case of digital radiography and ultrasonic testing. Terahertz inspection with pulsed excitation is reported as a source of many useful information about the internal structure of the dielectric material. Up to now ADR based on terahertz non-destructive evaluation systems was not utilized.

What role do people's attitudes toward social policies play for the politics of welfare state reform? This chapter contributes to a growing scholarship on policy responsiveness in welfare state research with a longitudinal comparative case study of the Bismarckian welfare states of France and Germany. Quantitative analyses of changes in mean attitudes as well as polarization and inequalities of attitudes based on the 1996, 2006, and 2016 waves of the International Social Survey Program (ISSP) Role of Government module are triangulated with a thick description of social policy changes. While recommodifying and defamilializing reforms in Germany transformed the welfare state fundamentally, there was more continuity in the French welfare state, in spite of a stronger focus on labor market activation policies. The quantitative results suggest that lower attitudinal stability toward the welfare state in Germany and lower polarization evoked a higher willingness for reform than in France, where more polarized attitudes and overall marginal changes in attitudes gave French governments less maneuverability in adopting reforms. In both countries, I find no evidence for an upper-class bias in policy responsiveness. In sum, my research supports the claim that change in public opinion toward the welfare state and diverging attitudes within societies play a role for the timing and direction of reforms.