Eddy current modelling using multi-layer perceptron neural networks for detecting surface cracks
A new method for computing fracture mechanics parameters using computational Eddy Current Modelling by Multi-layer Perceptron Neural Networks for detecting surface cracks. The method is based upon an inverse problem using an Artificial Neural Network (ANN) that simulates mapping between Eddy current...
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Gruppo Italiano Frattura
2018-06-01
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doaj-0fcb0dc25b0445998687aec21797076a2021-01-27T17:14:41ZengGruppo Italiano FratturaFrattura ed Integrità Strutturale1971-89932018-06-011245Eddy current modelling using multi-layer perceptron neural networks for detecting surface cracksSalaheddine Harzallah0R. Rebhi1M. Chabaat2A. Rabehi3University Built Environmental Research Lab., Civil Engineering Faculty, University of Sciences and Technology HouariBoumediene, B.P 32 El Alia Bab Ezzouar, Algiers 16111 Algeria.University Built Environmental Research Lab., Civil Engineering Faculty, University of Sciences and Technology HouariBoumediene, B.P 32 El Alia Bab Ezzouar, Algiers 16111 Algeria.University Built Environmental Research Lab., Civil Engineering Faculty, University of Sciences and Technology HouariBoumediene, B.P 32 El Alia Bab Ezzouar, Algiers 16111 Algeria.Laboratoire de Micro-électronique Appliquée, Université Djillali Liabès de Sidi Bel Abbés, BP 89, 22000 Sidi Bel Abbés, Algeria A new method for computing fracture mechanics parameters using computational Eddy Current Modelling by Multi-layer Perceptron Neural Networks for detecting surface cracks. The method is based upon an inverse problem using an Artificial Neural Network (ANN) that simulates mapping between Eddy current signals and crack profiles. Simultaneous use of ANN by MLP can be very helpful for the localization and the shape classification of defects. On the other side, it can be described as the task of reconstructing the cracks and damage in the plate profile of an inspected specimen in order to estimate its material properties. This is accomplished by inverting eddy current probe impedance measurements that are recorded as a function of probe position, excitation frequency or both. In eddy current nondestructive evaluation, this is widely recognized as a complex theoretical problem whose solution is likely to have a significant impact on the detection of cracks in materials https://www.fracturae.com/index.php/fis/article/view/20383D-FEM-ECArtificial Neural NetworkInverse ProblemsCracksMulti-layer Perceptron |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Salaheddine Harzallah R. Rebhi M. Chabaat A. Rabehi |
spellingShingle |
Salaheddine Harzallah R. Rebhi M. Chabaat A. Rabehi Eddy current modelling using multi-layer perceptron neural networks for detecting surface cracks Frattura ed Integrità Strutturale 3D-FEM-EC Artificial Neural Network Inverse Problems Cracks Multi-layer Perceptron |
author_facet |
Salaheddine Harzallah R. Rebhi M. Chabaat A. Rabehi |
author_sort |
Salaheddine Harzallah |
title |
Eddy current modelling using multi-layer perceptron neural networks for detecting surface cracks |
title_short |
Eddy current modelling using multi-layer perceptron neural networks for detecting surface cracks |
title_full |
Eddy current modelling using multi-layer perceptron neural networks for detecting surface cracks |
title_fullStr |
Eddy current modelling using multi-layer perceptron neural networks for detecting surface cracks |
title_full_unstemmed |
Eddy current modelling using multi-layer perceptron neural networks for detecting surface cracks |
title_sort |
eddy current modelling using multi-layer perceptron neural networks for detecting surface cracks |
publisher |
Gruppo Italiano Frattura |
series |
Frattura ed Integrità Strutturale |
issn |
1971-8993 |
publishDate |
2018-06-01 |
description |
A new method for computing fracture mechanics parameters using computational Eddy Current Modelling by Multi-layer Perceptron Neural Networks for detecting surface cracks. The method is based upon an inverse problem using an Artificial Neural Network (ANN) that simulates mapping between Eddy current signals and crack profiles. Simultaneous use of ANN by MLP can be very helpful for the localization and the shape classification of defects. On the other side, it can be described as the task of reconstructing the cracks and damage in the plate profile of an inspected specimen in order to estimate its material properties. This is accomplished by inverting eddy current probe impedance measurements that are recorded as a function of probe position, excitation frequency or both. In eddy current nondestructive evaluation, this is widely recognized as a complex theoretical problem whose solution is likely to have a significant impact on the detection of cracks in materials
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topic |
3D-FEM-EC Artificial Neural Network Inverse Problems Cracks Multi-layer Perceptron |
url |
https://www.fracturae.com/index.php/fis/article/view/2038 |
work_keys_str_mv |
AT salaheddineharzallah eddycurrentmodellingusingmultilayerperceptronneuralnetworksfordetectingsurfacecracks AT rrebhi eddycurrentmodellingusingmultilayerperceptronneuralnetworksfordetectingsurfacecracks AT mchabaat eddycurrentmodellingusingmultilayerperceptronneuralnetworksfordetectingsurfacecracks AT arabehi eddycurrentmodellingusingmultilayerperceptronneuralnetworksfordetectingsurfacecracks |
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1724320762285785088 |