Numerical modelling as a cost-reduction tool for probability of detection of bolt hole eddy current testing

Mandache, Catalin; Khan, M. Roshan; Fahr, A.; Yanishevsky, Marko

doi:10.1080/10589751003770118

Cited by 4 publications

(2 citation statements)

References 1 publication

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“…Due to the uncertainty caused by the small amount of available data, the third parameter, P3, was assumed to have one constant value. The non-linear and polynomial fitting functions in connection with eddy current signals for the POD have been used in the literature before [12] .…”

Section: Development Of the Advanced Pod Approach For Low-frequency Ementioning

confidence: 99%

Probability of detection for surface-breaking holes with low-frequency eddy current testing – a non-linear multi-parametric approach

Kanzler¹,

Müller²,

Pitkänen³

2014

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The evaluation of non-destructive testing (NDT) methods in terms of reliability is an increasing demand in various industries and applications. The probability of detection (POD) is the most frequently used method for this task. In the testing of holes with low-frequency eddy current testing, the frequently-used one-parametric POD approach cannot be used because the requirements, mainly the linearity, cannot be met. Therefore, the use of a multi-parametric non-linear regression approach to calculate the POD is proposed. Instead of numerical simulations, commonly used in multiparametric approaches, an analytical model is used. The goal of this work is to evaluate the reliability of the eddy current system for the testing of electron-beam welded copper canisters by calculating a POD with the help of different artificial hole-like defects. In this example, the multi-parametric non-linear regression approach is shown to be successful, enabling the combination of depth and diameter in the POD calculation.

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Section: Development Of the Advanced Pod Approach For Low-frequency Ementioning

confidence: 99%

Probability of detection for surface-breaking holes with low-frequency eddy current testing – a non-linear multi-parametric approach

Kanzler¹,

Müller²,

Pitkänen³

2014

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“…Among these NDT techniques, the eddy current nondestructive testing (ECNDT) method is a useful technique for detecting defects in conductive materials, especially in multi-layered structures. When using the other NDT techniques [4][5][6][7][8], it is widely recognized as being both a complex and critical problem. M In ECNDT, one of the principal challenges is to determine the size of deep defects in the multi-layered structures based on information contained in the signal representing the change in impedance of the coil as it scans over the specimen.…”

Section: Introductionmentioning

confidence: 99%

Quantitative estimating size of deep defects in multi-layered structures from eddy current NDT signals using improved ant colony algorithm

Ye¹,

Li²,

Qiu³

et al. 2014

Frattura Ed Integrità Strutturale

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Detection and quantitative estimation of deep defects in multi-layered structures is an essential task in a range of technological applications, such as maintaining the integrity of structures, enhancing the safety of aging aircraft, and assuring the quality of products. A novel approach to accurately quantify the two-dimensional axisymmetric deep defect size from eddy current nondestructive testing (NDT) signals is presented here. The method uses a finite element forward model to simulate the underlying physical process and an improved ant colony algorithm (IACA) to solve the inverse problem. Experiments are carried out. The performance comparison between the IACA method and the least square method is shown. The comparison results demonstrate the feasibility and validity of the IACA method. Between them, the IACA method gives a better estimation performance than the least square method at present.

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Bolt preload monitoring based on percussion sound signal and convolutional neural network (CNN)

Yang

Huo

2022

Nondestructive Testing and Evaluation

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Numerical modelling as a cost-reduction tool for probability of detection of bolt hole eddy current testing

Cited by 4 publications

References 1 publication

Probability of detection for surface-breaking holes with low-frequency eddy current testing – a non-linear multi-parametric approach

Probability of detection for surface-breaking holes with low-frequency eddy current testing – a non-linear multi-parametric approach

Quantitative estimating size of deep defects in multi-layered structures from eddy current NDT signals using improved ant colony algorithm

Bolt preload monitoring based on percussion sound signal and convolutional neural network (CNN)

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