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http://hdl.handle.net/123456789/2644
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Title: | PREDICTION OF FATIGUE CRACKS IN BEAMS USING ARTIFICIAL NEURAL NETWORKS |
Authors: | Gillich, G.R. Aman, A.T. Tufisi, C. |
Keywords: | fatigue cracks damage detection artificial neural networks natural frequencies |
Issue Date: | Oct-2022 |
Publisher: | Transilvania University Press of Braşov |
Citation: | http://scholar.google.ro/ |
Series/Report no.: | COMAT 2022;82-88 |
Abstract: | In their functioning time, most engineering structures are subjected to cyclic loading which can lead to the development of fatigue cracks that can propagate in time until the structure fails. Fatigue cracks in metals usually start from the surface of a structure, where the damage initiates as shear cracks. In the current paper, we demonstrate the possibility of evaluating two transverse cracks present in a steel cantilever beam by applying an intelligent algorithm with the help of MatLab software. The research demonstrates the possibility of detecting and locating the damages by employing the natural frequencies of the structure. |
URI: | http://hdl.handle.net/123456789/2644 |
ISSN: | 2457-8541 |
Appears in Collections: | COMAT 2022
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