Interactions of an eddy current sensor and a multilayered structure

Cung, Thanh Long; Joubert, Pierre-Yves; Vourch, E.; Larzabal, Pascal

doi:10.1049/el.2010.2611

Cited by 6 publications

(9 citation statements)

References 6 publications

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“…This quantity, the |DZ n |, hereafter is called the normalized impedance distance (NID) in this paper. As results published in a previous paper (Cung et al, 2010), experimentally, it appears that there is a linear relationship between NID and t a [equation ( 2)].…”

Section: Experimental Setup and Problem Formulationsupporting

confidence: 59%

“…The studied structure and its experimental setup are shown in Figure 1. The normalized impedance (Cung et al, 2010) of the sensor coupled with the multilayered assembly, denoted Z n , will be a function of the coating and rib thicknesses t c and t r and of the gap t a . We analyse the relationship between the air-gap t a and the difference of normalized impedance, which, at an excitation frequency f, is defined as:…”

Section: Experimental Setup and Problem Formulationmentioning

confidence: 99%

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A model-based approach for inspection of aeronautical multi-layered structures by eddy currents

Cung

Nguyen

Joubert

et al. 2019

COMPEL

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Purpose The purpose of this paper is to propose an approach, which is easy to implement, for estimating the thickness of the air layer that may separate metallic parts in some aeronautical assemblies, by using the eddy current method. Design/methodology/approach Based on an experimental study of the coupling of a magnetic cup core coil sensor with a metallic layered structure (consisting of first metal layer/air layer/second metal layer), which is confirmed by finite element modelling simulations, an inversion technique relying on a polynomial forward model of the coupling is proposed to estimate the air layer thickness. The least squares and the nonnegative least squares algorithms are applied and analysed to obtain the estimation results. Findings The choice of an appropriate inversion technique to optimize the estimation results is dependent on the signal-to-noise ratio of measured data. The obtained estimation error is smaller than a few percent, for both simulated and experimental data. The proposed approach can be used to estimate both the air layer thickness and the second metal layer thickness simultaneously/separately. Originality/value This model-based approach is easy to implement and available to all types of eddy current sensors.

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Section: Experimental Setup and Problem Formulationsupporting

confidence: 59%

Section: Experimental Setup and Problem Formulationmentioning

confidence: 99%

A model-based approach for inspection of aeronautical multi-layered structures by eddy currents

Cung

Nguyen

Joubert

et al. 2019

COMPEL

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“…Z is the impedance of the sensor, R0 and X0 are the resistance and the reactance of the uncoupled sensor respectively. In previous works, it has been shown both experimentally and computationally that the modulus of ∆Z is a function of the distance between parts [7]. More precisely, a multifrequency study enabled us to assess that i) there exists an optimal frequency range maximizing the sensor sensitivity towards the distance between parts, ii) only the modulus of ∆Z is significantly modified by the distance between parts, iii) the modulus of ∆Z vary linearly with the latter distance within the optimal frequency range, and iv) the variations of ∆Z as a function of the thickness of the bottom plate are nonlinear.…”

Section: Experimental Set-up and Multi-frequency Ec Datamentioning

confidence: 99%

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

2021

JST: ETSD

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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%.

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“…However, it has been shown in previous works [14] that the normalized impedance of the sensor coupled with the multilayered assembly, denoted Z nt , is a function of the coating and rib thicknesses t c , t r , and of the gap t, and is advantageously studied in the UID plane.…”

Section: Sensor and Target Interactionsmentioning

confidence: 99%

“…Among the solutions provided by the equations (14), only those corresponding to the actual rib thickness, noted act rl t , will be true and also equal to each other. As a consequence, the actual rib thickness may be estimated as the one such that the equations (14) …”

Section: Case C: T R Is Unknownmentioning

confidence: 99%

Eddy current evaluation of air–gaps in aeronautical multilayered assemblies using a multi-frequency behavioral model

2011

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current evaluation of air-gaps in aeronautical multilayered assemblies using a multi-frequency behavioral model. Measurement, Elsevier, 2011, 44 (6) ABSTRACTThis paper reports on the estimation of the air-gap thickness between parts in an aeronautical multilayered metallic assembly, by the means of the eddy current method. A behavioural multi-frequency modelling of the interactions between the used cup core sensor and the multilayered structure was developed thanks to the analysis of experimental data, completed with finite element electromagnetic computations. The elaborated model was used to estimate the air-gap thickness (in the range of 0 to 500 µm) of a multilayered structure featured by a metallic coating of known thickness (1.5 mm) and a distant metallic layer of unknown thickness (in the range 1.5 mm to 3.5 mm). The obtained estimation error is smaller than a few percents, either for simulated or experimental data.

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Interactions of an eddy current sensor and a multilayered structure

Cited by 6 publications

References 6 publications

A model-based approach for inspection of aeronautical multi-layered structures by eddy currents

A model-based approach for inspection of aeronautical multi-layered structures by eddy currents

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

Eddy current evaluation of air–gaps in aeronautical multilayered assemblies using a multi-frequency behavioral model

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