Multi-frequency Eddy Current Method Research Articles

Automated non-destructive testing of steel alloys microstructure based on multifrequency eddy current method

Technical Diagnostics and Non-Destructive Testing, 2022, №01. TEKHNICHESKAYA DIAGNOSTIKA I NERAZRUSHAYUSHCHIY KONTROL Quarterly scientific-technical and production journal. ISSN: 0235-3474. Established in 1989. Subscription index: 74475. State Registration Certificate KV 4787 of 09.01.2001. All rights reserved Publisher: B.E.Paton Electric Welding Institute, National Academy of Sciences of Ukraine. Main topics of the magazine: theoretical and practical articles on technical diagnosing and non-destructive testing; flaw detection, residual life of structures. Each issue features: scientific articles; manufacturing experiences; reviews; exhibitions, conferences; advertisements.

Extended Damage Detection and Identification in Aircraft Structure Based on Multifrequency Eddy Current Method and Mutual Image Similarity Assessment.

In this paper, a novel approach to Non-Destructive Testing (NDT) of defective materials for the aircraft industry is proposed, which utilizes an approach based on multifrequency and spectrogram eddy current method combined with an image analysis method previously applied for general-purpose full-reference image quality assessment (FR IQA). The proposed defect identification method is based on the use of the modified SSIM4 image quality metric. The developed method was thoroughly tested for various locations, sizes, and configurations of defects in the examined structure. Its application makes it possible to not only determine the presence of cracks but also estimate their size.

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%.

Application of Closed Magnetic Circuit Method for Evaluating the Stress Distribution along Depth Direction

Electromagnetic nondestructive evaluation method is feasible in assessing stress or residual stress levels in ferromagnetic structures, for there is a strong inherent correlation between the permeability and the stress. This study is based on the closed magnetic circuit method for testing stress distribution along depth. Firstly, a theory is proposed for describing the propagation of electromagnetic energy inside ferromagnetic materials. A layered model is established considering the electromagnetic field experienced different attenuation at different depths. And each layer is assumed to have the identical physical state. Then, multi-frequency eddy current method is proposed to testing the in-depth permeability variation and consequently the stress-depth profile. For simply using the convolution integral, a novel inversion algorithm is given to resolve the convolution integral. To apply the proposed method for testing the stress-depth profile, multi-frequency eddy current experiments are conducted through a four-point bending device; with the specimen material employed is 45# steel. Finally, map the experimental data fitting curve to the theoretical calculation curve, and hence can verify the proposed theory and the inversion algorithm.

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.

Investigation of new volumetric non-destructive techniques to characterise additive manufacturing parts

The assessment of the potential of various non-destructive methods to characterise additive manufactured dense and lattice parts was investigated. The Archimedes’ and gas pycnometric methods for density measurements of both types of structures are presented as well as the percentage of cells in lattice structures. A multi-frequency eddy current method for electrical conductivity measurements of lattice structures is also presented. Finally, C-scan ultrasound method for the characterisation of dense parts was investigated. The advantages and limitations of each method are underlined.

Massive Multi-Frequency Eddy Current Method for Clad Material Inspection

The aim of this paper is to present a massive multi-frequency method for detection of cracks in clad materials. A system excited by a voltage waveform obtained as a sum of many sinusoidal components is proposed for this purpose. Studies show that, the multi-frequency method can be successfully used for detection and assessment of the defects depth in such kind of materials. The experimental verification is done and selected results of measurements are presented. with a depth of changes in the tested structure. That can be useful in applications such as measuring the thickness of conductive coatings on conductive base metal, detection and identification flaws in the material surface, differentiating between flaws in various layers of built-up structure. The additional advantages is that utilization of numerous frequency components in the excitation signal allow to fully test the structure as every single frequency consists independent information. Therefore, impact of noise can be reduced. Moreover presented method is much faster than Swept Frequency Methods and can be used complementary or as a substitute for the standard ECT.

Inspection of aluminum alloys by a multi-frequency eddy current method

The paper proposes an experimental method of material inspection, which is based on digital processing of multi-frequency eddy current measurement data. The influences of various factors (conductivity, the gap between the sample surface and the sensor, the thickness of the sample) on the obtained hodographs are examined by taking the aluminum alloys for example, and the possibility of separation of various factors is analyzed. The results obtained are indicative of how much promise the proposed method offers for the inspection and testing of products made of aluminum alloys.

Natural crack recognition using inverse neural model and multi-frequency eddy current method

In this paper a Multi-Frequency Excitation and Spectrogram Eddy Current System and an inverse neural model were used to detect and identify natural flaws in steam generator tubes. It is shown that the applied dynamic neural model of the ECT sensor offers very high speed of operation and guarantees reliability of the recognition results.

New methods of signal excitation and processing in magneto-inductive testing of structures and alloys

Abstract This paper describes some results of applying noise excitation to eddy current testing. Pseudo random binary sequences (PRBS) were used as a noise equivalent. The advantage of this technique compared with conventional methods is mainly the simplicity of the equipment used. It is possible to produce a device using noise excitation on the basis of a microcalculator. Also, this technique gives a direct comparison between the reference object and the object under test as in the well known CS (controlled signals) method. The performance of the PRBS method is compared with a multifrequency eddy current method by solving the problem of separating various grades of steel. Both methods show nearly the same results.

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.