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Vera Barat, Artem Marchenkov and Sergey Elizarov
This article is devoted to materials testing by the acoustic emission (AE) method, which is the analysis of models and diagnostic parameters to assess the probability of detection of a defect in steel structures. The paper proposes to evaluate the emissi...
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Maria Barroso-Romero, Daniel Gagar, Shashank Pant and Marcias Martinez
Acoustic Emission (AE) monitoring can be used to detect and locate structural damage such as growing fatigue cracks. The accuracy of damage location and consequently the inference of its significance for damage assessment is dependent on the wave propaga...
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Arvin Ebrahimkhanlou and Salvatore Salamone
This paper introduces two deep learning approaches to localize acoustic emissions (AE) sources within metallic plates with geometric features, such as rivet-connected stiffeners. In particular, a stack of autoencoders and a convolutional neural network a...
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