Artificial Immune Systems with Negative Selection Applied to Structural Integrity Monitoring in a Metallic Bridge
DOI:
https://doi.org/10.33448/rsd-v11i15.37527Keywords:
Artificial Immune Systems; Negative Selection Algorithm; Structural Integrity Analysis; Metal bridge.Abstract
In this paper presents an artificial intelligence system based on artificial immune systems for analyzing the structure of a metal bridge. Inspired by a biological process, the negative selection algorithm is used to carry out the identification and characterization of structural failures. This tool will help identify the maintenance, configurations of structures, the way to identify failures, in order to ensure the health quality of the structure and carry out security decisions. To validate the methodology, were used a real data obtained from laboratory experiment, and from this, several situations were generated (normal and fault conditions), obtaining a database of signals, which were analyzed by the method proposed. The results obtained by the negative selection algorithm are efficient and robustness. It is worth mentioning that artificial intelligence with signal processing allows for a higher quality in the diagnosis. Thus, this article contributes to the lines of research in structural health monitoring and artificial intelligence, presenting a very efficient methodology.
References
Bradley, D. W., & Tyrrell, A. M. (2002). Immunotronics - Novel Finite-State-Machine Architectures with Built-In Self-Test Using Self-Nonself Differentiation. IEEE Trans. on Evolutionary Computation. 6 (3), 227-238.
Chandrashekhar, M., & Ganguli, R. (2009). Structural damage detection using modal curvature and fuzzy logic, Structural Health Monitoring, 8 (1), 267-282.
Chavarette, F. R., et al. (2021). Reconhecimento de falhas estruturais utilizando sistema imunológico artificial Wavelet. Colloquium Exactarum, 12 (1), 82-88.
Chaves, J. S., Lopes, M. L. M., Chavarette, F. R., & Lima, F. P. A. (2017). Rede Neural Artificial ARTMAP-Fuzzy Aplicada no Reconhecimento de Falhas Estruturais. Revista Iberoamericana de Ingeniería Mecánica, 21 (1), 03-11.
Doebling, S. W., Farrar, C., Prime, M. B., & Shevitz, D. W. (1996). Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in their Vibration Characteristics: A Literature Review.
Espion, B. (2012). The Vierendeel bridges over the Albert Canal, Belgium – their significance in the story of brittle failures. Steel Construction, 5 (1), 1-6.
Franco, V. R. (2009). Monitoramento da integridade de estruturas aeronáuticas. 2009. 205 f. Dissertação (Mestrado em Engenharia Mecânica) - Faculdade de Engenharia, Universidade Estadual Paulista - UNESP, Ilha Solteira.
Forrest, S., Perelson, A., Allen, L., & Cherukuri, R. (1994). Self-Nonself Discrimination in a Computer, Proc. of IEEE Symposium on Research in Security and Privacy. 202-212.
Gonçalves, D. R., Moura Junior, J. R. V., & Pereira, P. E. C. (2020). Monitoramento de integridade estrutural baseado em impedância eletromecânica utilizando o método de krigagem ordinária. 36 (2).
Gonsalez, C. G. (2012). Metodologias para reconhecimento de padrões em sistemas de SHM utilizando a técnica da impedância eletromecânica (E/M). 2012. 117 f. Dissertação (Mestrado em Engenharia Mecânica) - Faculdade de Engenharia, Universidade Estadual Paulista - UNESP, Ilha Solteira.
Hall, S. R. (1999). The effective management and use of structural health data. Proc. of International Workshop on Structural Health Monitoring, VirginiaTech Publisher, 265-275.
Lima, F. P. A. (2014). Monitoramento e Identificação de Falhas em Estruturas Aeronáuticas e Mecânicas Utilizando Técnicas de Computação Inteligente. 2014. 72 f. Dissertação (Mestrado em Engenharia Mecânica) - Faculdade de Engenharia, Universidade Estadual Paulista - UNESP, Ilha Solteira.
Lima, F. P. A., Lotufo, A. D. P., & Minussi, C. R. (2013). Artificial Immune Systems Applied to Voltage Disturbance Diagnosis in Distribution Electrical Systems, PowerTech-2013, Grenoble, France, 1-6.
Lima, F. P. A., & Souza, S. S. F. (2016). Rede neural artificial ARTMAP-Fuzzy-Wavelet aplicada no reconhecimento de falhas estruturais. Revista Engenharia em Ação UniToledo, Araçatuba, SP, 1 (1), 36-53.
MATLAB 7.8 version, Mathworks Company.
Meireles, A. P. C. (2010). Levantamento e diagnóstico de uma ponte metálica antiga. 2010. Dissertação (Mestrado Integrado em Engenharia Civil) - Faculdade de Engenharia da Universidade do Porto, Porto, Portugal.
Mundo Educação. < https://mundoeducacao.uol.com.br/fisica/ponte-tacoma-narrows.htm>.
Oliveira, D. C., Chavarette, F. R., & Outa, R. (2020). Monitoramento de integridade estrutural de um rotor utilizando algoritmos de sistemas imunológicos artificiais com seleção negativa e seleção clonal. Research, Society and Development, 9 (7).
Palaia, L. (2007). Structural Failure Analysis of timber floors and roofs in ancient buildings at Valencia (Spain). Proc. of International Conference on Mechanical Behavior and Failures of the Timber Structures, Florence, 1–11.
Roseiro, L., Ramos, U., & Leal, R. (2005). Neural Networks in Damage Detection of Composite Laminated Plates, Proc. of the 6th International Conference on Neural Networks, 115-119.
Silva, S., Dias Júnior, M., & Lopes Júnior, V. (2008). Structural health monitoring in smart structures through time series analysis. Structural Health Monitoring, London, 7 (3), 231-244.
Souza, S. S. F., Campos, M. B. P., Chavarette, F. R., & Lima, F. P. A. (2021). A New Approach Experimental to Diagnosis of The Failures in Mechanical Structures Using the Artificial Immune Algorithm with Negative Selection. Brazilian Journal of Development, 7 (1), 66372-66392.
Tebaldi, A., Coelho, L. S., & Lopes Junior., V. (2006). Detecção de falhas em estruturas inteligentes usando otimização por nuvem de partículas: fundamentos e estudo de casos. Revista Controle & Automação, São Paulo, 17 (3), 312–330.
Vitório, J. A. P. (2021). Uma análise das falhas estruturais em Obras de Arte Especiais. Proc. of XII Congresso Brasileiro de Pontes e Estruturas (CBPE). Universidade de Pernambuco.
Xiang-Jun, C., Zhan-Feng, G., & Qiang, G. (2010). Application of wavelet analysis in vibration signal processing of bridge structure. Proc. of International Conference on Measuring Technology and Mechatronics Automation, VirginiaTech Publisher, 671–674.
Wang, F. L., Chan, T. H. T., Thambiratnam, D. P., & Tan, A. C. C. (2013). Damage diagnosis for complex steel truss bridges using multi-layer genetic Algorithm. Journal of Civil structural Health Monitoring, Inglaterra, 3 (2), 117–217.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Alyson Aláx Alves dos Santos ; Fábio Roberto Chavarette; Simone Silva Frutuoso de Souza
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
