2023
DOI: 10.1155/2023/8829298
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Detection, Localization, and Quantification of Damage in Structures via Artificial Neural Networks

Daniele Kauctz Monteiro,
Letícia Fleck Fadel Miguel,
Gustavo Zeni
et al.

Abstract: This paper presents a structural health monitoring method based on artificial neural networks (ANNs) capable of detecting, locating, and quantifying damage in a single stage. The proposed framework employs a supervised neural network model that uses input factors calculated by modal parameters (natural frequencies or mode shapes), and output factors that represent the damage situation of elements or regions in a structural system. Unlike many papers in the literature that test damage detection methods only in … Show more

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