| Full text | |
| Author(s): |
Borges Lourenco, Rodrigo Francisco
[1]
;
Outa, Roberto
[2]
;
Chavarette, Fabio Roberto
[3]
;
Goncalves, Aparecido Carlos
[1]
Total Authors: 4
|
| Affiliation: | [1] UNESP Univ Estadual Paulista, Dept Mech Engn, Fac Engn Ilha Solteira, BR-15385000 Ilha Solteira - Brazil
[2] Fac Technol Aracatuba, Dept Biofuels, Av Prestes Maia 1764, BR-16052045 Aracatuba - Brazil
[3] UNESP Inst Quim, Dept Engn Fis & Matemat, Rua Prof Francisco Degni 55, BR-14800060 Araraquara, SP - Brazil
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | JOURNAL OF APPLIED AND COMPUTATIONAL MECHANICS; v. 7, n. 3, p. 1764-1773, SUM 2021. |
| Web of Science Citations: | 0 |
| 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 for structural analysis. (AU) | |
| FAPESP's process: | 19/10515-4 - Prognosis and mechanical structure failure detection using natural computing |
| Grantee: | Fábio Roberto Chavarette |
| Support Opportunities: | Regular Research Grants |