Analysis of Structural Integrity Using an ARTMAP-Fuzzy Artificial Neural Network

• Autor(a) principal: Santos e Souza, Adriano dos [UNESP]
• Data de Publicação: 2014
• Outros Autores: Chavarette, Fabio Roberto, Anjos Lima, Fernando Parra dos [UNESP], Lopes, Mara Lucia Martins, Frutuoso de Souza, Simone Silva, Zhang, X, Zhang, B., Jiang, L., Xie, M.
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.4028/www.scientific.net/AMR.838-841.3287; http://hdl.handle.net/11449/117549
• topic: Analysis of Structural Integrity; Building Structure; Artificial Neural Networks; Adaptive Resonance Theory

This paper presents the application of artificial neural networks in the analysis of the structural integrity of a building. The main objective is to apply an artificial neural network based on adaptive resonance theory, called ARTMAP-Fuzzy neural network and apply it to the identification and characterization of structural failure. This methodology can help professionals in the inspection of structures, to identify and characterize flaws in order to conduct preventative maintenance to ensure the integrity of the structure and decision-making. In order to validate the methodology was modeled a building of two walk, and from this model were simulated various situations (base-line condition and improper conditions), resulting in a database of signs, which were used as input data for ARTMAP-Fuzzy network. The results show efficiency, robustness and accuracy.