Open AccessCrack prediction in beam-like structure using ANN based on frequency analysis
Author(s) -
Meriem Seguini,
Djamel Nedjar,
Djilali Boutchicha,
Samir Khatir,
Magd Abdel Wahab
Publication year - 2021
Publication title -
frattura ed integrità strutturale
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.368
H-Index - 19
ISSN - 1971-8993
DOI - 10.3221/igf-esis.59.02
Subject(s) - structural engineering , matlab , beam (structure) , artificial neural network , finite element method , sensitivity (control systems) , software , numerical analysis , materials science , computer science , engineering , mathematics , artificial intelligence , mathematical analysis , electronic engineering , programming language , operating system
The dynamic experimental and numerical analysis of cracked beams has been studied with the aim of quantifying the influence of depth crack on the dynamic response of steel beams. Artificial Neural Method ANN has been used where a numerical simulation was improved in Matlab. A finite element model has also been developed by using the Ansys software, and the obtained results were compared with exact crack length. The study takes into account different hidden layer values in order to determine the sensitivity of the predicted crack depth. The results show that the response of the beam (frequencies) is strongly related to the crack depth which significantly affects the beam behavior, especially when the crack is very deep where the ANN allows us to identify the crack in lower computational time. Based on the provided results, we can detect that the effect of hidden layer size can affect the results.