Analysis and Recognition of Standards in Intelligent Hybrid Systems using Natural Computing

• Autor(a) principal: Lourenço, Rodrigo Francisco Borges [UNESP]
• Data de Publicação: 2021
• Outros Autores: Outa, Roberto, Chavarette, Fábio Roberto [UNESP], Gonçalves, Aparecido Carlos [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.22055/jacm.2021.37798.3089; http://hdl.handle.net/11449/229176
• topic: hybrid system; natural computing; perceptron network; predictive system; Vibration

Abstract. This work shows the application of one of the techniques of bioengineering, the perceptron network in the detection of system failures, and also allows the use of the perceptron network technique in choosing the location of the best sensor to be used in the dynamic system. The application of the perceptron network was adopted because it is considered the best binary linear classifier. This work is considered multidisciplinary and difficult to develop. The final result demonstrates a severe application of pre-processing and processing, until the classification and grouping of signals in the two phases of the work. Through the results found, this work can be considered successful and can be applied in several areas of engineering forstructural analysis.