Multifrequency Eddy Current Research Articles

Complementary Methods for the Assessment of the Porosity of Laser Additive-Manufactured Titanium Alloy.

The method of making parts through additive manufacturing (AM) is becoming more and more widespread due to the possibility of the direct manufacturing of components with complex geometries. However, the technology's capacity is limited by the appearance of micro-cracks/discontinuities during the layer-by-layer thermal process. The ultrasonic (US) method is often applied to detect and estimate the location and size of discontinuities in the metallic parts obtained by AM as well as to identify local deterioration in structures. The Ti6Al4V (Ti64) alloy prepared by AM needed to acquire a high-quality densification if remarkable mechanical properties were to be pursued. Ultrasonic instruments employ a different type of scanning for the studied samples, resulting in extremely detailed images comparable to X-rays. Automated non-destructive testing with special algorithms is widely used in the industry today. In general, this means that there is a trend towards automation and data sharing in various technological and production sectors, including the use of intelligent systems at the initial stage of production that can exclude defective construction materials, prevent the spread of defective products, and identify the causes of certain instances of damage. Placing the non-destructive testing on a completely new basis will create the possibility for a broader analysis of the primary data and thus will contribute to the improvement of both inspection reliability and consistency of the results. The paper aims to present the C-scan method, using ultrasonic images in amplitude or time-of-flight to emphasize discontinuities of Ti64 samples realized by laser powder-bed fusion (L-PBF) technology. The analysis of US maps offers the possibility of information correlation, mainly as to flaws in certain areas, as well as distribution of a specific flaw in the volume of the sample (flaws and pores). Final users can import C-scan results as ASCII files for further processing and comparison with other methods of analysis (e.g., non-linear elastic wave spectroscopy (NEWS), multi-frequency eddy current, and computer tomography), leading to specific results. The precision of the flight time measurement ensures the possibility of estimating the types of discontinuities, including volumetric ones, offering immediate results of the inspection. In situ monitoring allows the detection, characterization, and prediction of defects, which is suitable for robotics. Detailing the level of discontinuities at a certain location is extremely valuable for making maintenance and management decisions.

Microstructure and mechanical properties evaluation of automotive plate steel based on micromagnetic NDT technologies

Micromagnetic NDT technologies help to elucidate the microstructural features/macro-mechanical properties, which are associated with the magnetic properties of the ferromagnetic material. In this investigation, magnetic Barkhausen noise (MBN), magnetic incremental permeability (MIP) and multi-frequency eddy current (MFEC) methods were applied to evaluate the microstructure and mechanical properties of automotive plate steels. The ratio of pearlite area to total crystal area (α) and the average grain area of pearlite (β) in automotive plate steel samples were extracted by optical microscopy (OM) and an improved image feature extraction algorithm based on sparse autoencoders (SAE). The correlation between the micromagnetic characteristics of three NDT methods and the microstructural features of automotive plate steels was also investigated. Based on micromagnetic characteristics, the random forest (RF) regression model was utilized to predict the microstructure and mechanical properties of samples.

Evaluation of Loose Assemblies Using a Multi-frequency Eddy Current Method and Artificial Neural Networks

The paper deals with the non-destructive evaluation of the airgap existing between parts in loose metallic assemblies, using the eddy current (EC) method. In this study, the relationship between the variations of the impedance of a ferrite-cored coil sensor and an assembly featuring two aluminum plates is analyzed. Then artificial neural networks, based on statistical learning of the relationship between a sensor and an assembly are proposed and developed using both simulated and measured multi-frequency EC data, so as to estimate the distance between the assembly parts in a range from 0 µm to 500 µm. For the neural network built on experiment data, the inaccuracy of obtained results is smaller than 1.06%.

Lift-off invariant inductance of steels in multi-frequency eddy-current testing

Eddy current testing can be used to interrogate steels but it is hampered by the lift-off distance of the sensor. Previously, the lift-off point of intersection (LOI) feature has been found for the pulsed eddy current (PEC) testing. In this paper, a lift-off invariant inductance (LII) feature is proposed for the multi-frequency eddy current (MEC) testing, which merely targets the ferromagnetic steels. That is, at a certain working frequency, the measured inductance signal is found nearly immune to the lift-off distance of the sensor. Such working frequency and inductance are termed as the lift-off invariant frequency (LIF) and LII. Through simulations and experimental measurements of different steels under the multi-frequency manner, the LII has been verified to be merely related to the sensor parameters and independent of different steels. By referring to the LIF of the test piece and using an iterative inverse solver, one of the steel properties (either the electrical conductivity or magnetic permeability) can be reconstructed with a high accuracy.

Application of a New Inversion Algorithm Based on Multi-Layer Model Hypothesis for Testing Stress-Depth Profiles by Multi-Frequency EC Method

Since the permeability of ferromagnetic materials is sensitive to the stress changes, it is feasible to acquire the stress level through detecting the change in permeability. In this study, to explore the distribution of stress or residual stress along the depth direction, a multi-layer model was established and a new inversion algorithm was proposed; and the hypothesis of uniformity of the material’s physical properties for each layer was introduced. Under laboratory conditions, the four-point bending experiment was then implemented with a sample of 45# steel. Global Fourier series fitting based on the least-squares method was used for signal process. The amplitude ratio of the induced voltage to the excitation current was extracted. The effective permeability and the associated hysteresis angle at the 0.25 mm deflection were calculated and presented good regular variations. Finally, under the 0.25 mm deflection, the effective permeability change along the depth was obtained, and the inversely fitted curve was consistent with the theoretical curve. It is verified that the sensor has good robustness by adding deviation of the detection depth. Thereby, it is feasible to test stress or residual stress as a function of depth by multi-frequency eddy current (EC) method.

Inversion of Distance and Magnetic Permeability Based on Material-Independent and Liftoff Insensitive Algorithms Using Eddy Current Sensor

Eddy current sensors can be used to test the characteristics and measure the parameters of the conductive samples. As the main obstacle of the multifrequency eddy current (MEC) sensor, the liftoff distance affects the effectiveness and accuracy of the measurement. In this article, a material-independent algorithm has been proposed for the restoration of the liftoff distance when using the MEC sensor, which is based on the approximation under the thin-skin effect. Experiment testing on the performance of the proposed method is presented. The results show that from the dual-frequency inductance, the liftoff distance could be restored with a maximum error of 0.24 mm for the distance up to 12 mm. Besides, the derived liftoff distance is used for the inversion of the magnetic permeability. Based on a liftoff insensitive inductance (LII) feature, the magnetic permeability of steels can be inversed in an iterative manner, with an error of less than 0.6 % for the liftoff distance up to 12 mm.

Novel Multifrequency Eddy Current NDT Signal Inversion Scheme for Aerostructures

Abstract Flaw profile characterization from nondestructive evaluation measurements is a typical nondestructive testing (NDT) inverse problem. Flaw profiling, particularly in aerospace industry, is important, as it is a decision tool to evaluate the air worthiness of the aerostructures. Accurate flaw profiling thus ensures aircraft safety through the timely implementation of cost-effective replacement/repair actions. Eddy current (EC) NDT data acquired at multiple frequencies contain complementary information about the flaws due to the skin effect phenomenon. However, finding the exact contribution of each measurement mode while determining the solution to the inverse problem is considerably challenging. In the reported research work, a novel multifrequency EC data-based polynomial model is formulated to solve the inverse problem. The weight (coefficient) of each measurement mode in the polynomial model is computed using nonlinear optimization techniques. Actual NDT data of a retired aircraft containing mutually exclusive training and test databases has been used as a case study. Data fusion (DF)-based inversion results are compared to the results acquired using individual measurement mode data. The improved results with DF indicate the efficacy of the proposed technique.

Real-Time Processing of Multifrequency Eddy Currents Testing Signals: Design, Implementation, and Evaluation

The design, implementation, and evaluation of a real-time digital signal processing architecture to generate and process multifrequency signals for eddy currents testing is described in this paper. This architecture is implemented on a dedicated instrument whose processing core is a field-programmable gate array. Stimulus generation is achieved using direct digital synthesis with some important improvements to reduce spurious frequency components. An in-phase and in-quadrature demodulation scheme is implemented to estimate the real and imaginary parts of the probe output signal. A cascaded integrator comb decimator is used to lower the sampling frequency and then allow narrowband filtering with low resources. The proposed architecture is able to generate and process the stimulus and input data at 125 MSamples/s and to estimate the input data components at 1.25 MSamples/s rate for eddy-currents with multiple simultaneous testing frequencies between 2.5 kHz and 10 MHz. Experimental validation is performed using a set of synthetic defects and two stimulus with different spectral composition.

Nondestructive evaluation of loose assemblies using multi-frequency eddy currents and artificial neural networks

This paper considers the problem of the evaluation of metallic assemblies in an aeronautical context, by means of a non-invasive method. The problems lies in the estimation of the distance separating two aluminum plates representative of a loose assembly (up to 300 µm), the top plate being possibly of unknown thickness ranging from 1 to 8 mm. To do so, the eddy current (EC) method is chosen, because it allows non-contact evaluation of conducting media to be carried out, which is sensitive to electrical conductivity changes in the part under evaluation, and hence to the presence of an air gap between parts. The problem falls into the category of evaluation of a multilayered conductive structure starting from EC data, which is an ill-posed problem. In order to bypass these difficulties, as well as to deal with the uncertainties that may be introduced by the experimental set-up, a ‘non-model’ approach is implemented by means of an artificial neural network (ANN). The latter is elaborated in a statistical learning approach starting from the experimental EC data provided by a ferrite cored coil EC probe used to investigate an assembly mockup of adjustable configuration. Moreover, in order to build a learning database allowing a robust and accurate ANN to be elaborated, as well as to deal with assemblies of unknown thicknesses, we consider EC data obtained at different frequencies chosen in an adjusted frequency bandwidth, experimentally determined so as to optimize the sensitivity toward the presence of an air gap between parts. The implementation of the proposed approach for distances between parts ranging from 60 to 300 µm provided estimated root mean square errors ranging from 7 μm up to 50 µm for the estimation of the distance between parts, and ranging from 20 µm up to 1.4 mm for the estimation of the top plates, ranging from 1 to 8 mm, respectively.

Theoretical model-based quantitative optimisation of numerical modelling for eddy current NDT

Eddy current (EC) nondestructive testing (NDT) is one of the most widely used NDT methods. Numerical modelling of NDT methods has been used as an important investigative approach alongside experimental and theoretical studies. This paper investigates the set-up of numerical modelling using finite-element method in terms of the optimal selection of element mesh size in different regions within the model based on theoretical analysis of EC NDT. The modelling set-up is refined and evaluated through numerical simulation, balancing both computation time and simulation accuracy. A case study in the optimisation of the modelling set-up of the EC NDT system with a cylindrical probe coil is carried out to verify the proposed optimisation approach. Here, the mesh size of the simulation model is set based on the geometries of the coil and the magnetic sensor, as well as on the skin depth in the sample; so the optimised modelling set-up can be useful even when the geometry of EC system, the excitation frequency or the pulsed width is changed in multi-frequency EC, sweep-frequency EC or system and pulsed EC. Furthermore, this optimisation approach can be used to improve the trade-off between accuracy and the computation time in other more complex EC NDT simulations.

Fast analytical modelling for pulsed eddy current evaluation

Numerical simulations of electromagnetic non-destructive evaluation (ENDE) can be time-consuming in comparison to analytical methods which provide fast closed-form solutions to the ENDE problems. In this paper, the Truncated Region Eigenfunction Expansion (TREE) modelling is extended to solve problems of pulsed eddy current (PEC) evaluation from the traditional multifrequency eddy current. The Fourier transform is employed to make the TREE feasible for solutions to PEC problems in both time and frequency domains. Moreover, because PEC employs magnetic field sensors/arrays to quantify magnetic field, the magnetic field signals from solid-state magnetic field sensors have been simulated using the extended TREE. It has been found that the predicted signals using the extended TREE has good agreement with the experimental results. Consequently, the established model can not only offer an effective solution in terms of faster simulation time and higher computational accuracy, but also be used for PEC evaluation in industry and in the inverse process for exploring the structural and electrical information of stratified conductive specimens during real-time monitoring.

Thickness measurement of non-magnetic plates using multi-frequency eddy current sensors

A robust feature in multi-frequency eddy current (MEC) testing has been found that can be directly linked to the thickness of the plate under test. It is shown mathematically that the peak frequency of the imaginary part of the inductance change when an air-cored coil is placed next to a non-magnetic metallic plate is inversely proportional to the thickness of the plate for a given material. Experimental results indicate that this relationship also holds for a ferrite-cored U-shaped coil. In addition, this peak frequency has been shown to be relatively independent of lift-off variations. Use of this new feature provides a fast and accurate method to gauge the thickness of plates. Measurements made for a sample air-cored and ferrite U-cored coil next to copper and aluminium plates of various thicknesses verified the proposed method.

Volumetric inspection of moderately thick austenitic stainless steels by multifrequency eddy currents

This paper describes the initial phase of a project to develop eddy-current methods to inspect welds joining sections of austenitic stainless steel pipe having walls up to 13 mm (0.5 in.) thick. The objective of this phase was to demonstrate the feasibility of detecting and characterizing flaws in austenitic stainless steel base metals. These materials and welds present challenging eddy-current problems because of their relatively large thickness and ferromagnetism. Multiparameter analysis shows that a reflection coil probe operated with three discrete driver frequencies and phase detection can locate and size a cracklike defect in a single conductor in the presence of variations in conductor resistivity, permeability, and thickness and in the probe-conductor spacing (liftoff). Experiments were performed with a modular three-frequency instrument. Flat-plate specimens of types 304L and 347 stainless steel machined to 12.7 to 15.9 mm thickness simulated pipe walls; saw-cut slots 10 to 30% of nominal specimen thickness simulated cracklike defects. The same slots were used in duplicate experiments as near-side (directly under the test probe) or far-side (in the face opposite the probe) defects. Flaw detection and characterization capability was demonstrated by a series of experimental measurements fitted to specimen properties by least squares techniques. The quality of the fit determined the expected accuracy of measurement. Comparison of accuracy estimates determined the best choice of operating frequencies. From the 1,2,5 sequence of frequencies between 0.5 and 20 kHz, the optimum set of operating frequencies was selected to be 0.5, 2, and 10 kHz. Estimates of measurement accuracy for combined near- and far-side defect cases were: plate thickness, 0.74 mm; probe liftoff, 0.03 mm; defect location (depth of material above defect), 3.48 mm; and defect size (vertical slot depth), 1.09 mm. A few property values were back-calculated from instrument readings; the errors in these values were somewhat larger than the measurement accuracy estimates because of instrument drift and the absence of calibration circuits.

The application of multi-frequency eddy currents to testing ferromagnetic metals

This paper describes a multi-frequency eddy current method in which signals of two different frequencies are applied, and the corresponding coil impedances are measured, in rapid succession. The method is highly suitable for testing ferromagnetic metals for which diffiulties arise with the existing multi-frequency eddy-current methods.