Introduction to the ACTA IMEKO issue dedicated to selected papers presented in the 18th IMEKO TC4 Symposium

Ramos, Pedro M.

doi:10.21014/acta_imeko.v1i1.33

ACTA IMEKO

2012

DOI: 10.21014/acta_imeko.v1i1.33

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Introduction to the ACTA IMEKO issue dedicated to selected papers presented in the 18th IMEKO TC4 Symposium

Pedro M. Ramos

Abstract: This manuscript is a brief introduction to the ACTA IMEKO issue dedicated to selected papers presented in the 18<sup>th</sup> IMEKO TC4 Symposium which took place in Natal, Brazil in September 2011 together with IX Semetro.

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Defect Reconstruction Using Multilayer Perceptron for Regression and Classification Tasks Based On Eddy Current Signatures

Barrarat,

Helifa,

Lefkaier

et al. 2024

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The safety of engineering structures can be significantly compromised by cracks resulting from manufacturing procedures or prior loading, potentially leading to severe and catastrophic industrial accidents. Therefore, it is crucial to accurately and quantitatively characterize cracks in such structures. One common technique for detecting defects in metallic structures is eddy current testing (ECT). This paper proposes a method for the reliable estimation of crack shape and dimensions in conductive materials using the principles of ECT combined with a machine learning algorithm. First, numerical simulations are used to examine the relationship between the detection signature and the crack length and depth. Then, an artificial neural network based on a machine learning technique is employed to inversely characterize the cracks. The predicted results demonstrate that the crack length, depth, and shape can be accurately determined by the proposed algorithm. These findings, obtained using various specimens with known cracks, validate the applicability of the proposed approach for crack characterization.

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Defect Reconstruction Using Multilayer Perceptron for Regression and Classification Tasks Based On Eddy Current Signatures

Barrarat,

Helifa,

Lefkaier

et al. 2024

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The Evaluation of Electric Power by Separate Analysis of Fourier Transform Components

Kostiukov

2021

LEPE

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This paper presents a substantiation of an approach for the evaluation of components of apparent power and intended to simplify the computational procedures which usually should be implemented in order to process the preliminary sampled waveform of instantaneous power. The results of carried out studies have shown that both active and reactive power can be calculated by the analysis of calculated components of sine and cosine Fourier transforms. This paper also presents the discussion of restrictions, which should be imposed on the duration of the analyzed signal and on frequencies of the auxiliary trigonometric functions, which are applied in order to calculate components of Fourier transform which are used for the evaluation of active and reactive power. The compliance with these restrictions allows us to eliminate the undesirable bias of active and reactive power estimation caused by the refusal from the decomposition of the analyzed waveform of the instantaneous power by applying the complete system of orthogonal trigonometric functions, as the evaluation of components of the apparent power is attained based on separate analysis of sine and cosine Fourier transforms calculated for the analyzed signal. The results of carried out simulations illustrate the frequency dependencies of sine Fourier transform calculated for the case of compliance with the restrictions, which allow to attain the highest accuracy of estimation and for the case when the duration of analyzed signal does not fit these restrictions.

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Introduction to the ACTA IMEKO issue dedicated to selected papers presented in the 18th IMEKO TC4 Symposium

Abstract: This manuscript is a brief introduction to the ACTA IMEKO issue dedicated to selected papers presented in the 18<sup>th</sup> IMEKO TC4 Symposium which took place in Natal, Brazil in September 2011 together with IX Semetro.

Cited by 2 publications

References 11 publications

Defect Reconstruction Using Multilayer Perceptron for Regression and Classification Tasks Based On Eddy Current Signatures

Defect Reconstruction Using Multilayer Perceptron for Regression and Classification Tasks Based On Eddy Current Signatures

The Evaluation of Electric Power by Separate Analysis of Fourier Transform Components

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