Volume 21, Issue 2 (9-2026)
IJMSI 2026, 21(2): 79-91 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Feliciani Merizio I, Chavarette F R, Mendonça Faria H A, Rathour L, Narayan Mishra L. Damage Detection in a Pipe Using an Artificial Immune System Optimized by the Clonal Selection Algorithm. IJMSI 2026; 21 (2) :79-91
URL: http://ijmsi.ir/article-1-2332-en.html
URL: http://ijmsi.ir/article-1-2332-en.html
Igor Feliciani Merizio 
, Fábio Roberto Chavarette , Henrique Antônio Mendonça Faria , Laxmi Rathour , Lakshmi Narayan Mishra
, Fábio Roberto Chavarette , Henrique Antônio Mendonça Faria , Laxmi Rathour , Lakshmi Narayan Mishra
Abstract:
This work presents an innovative Structural Health Monitoring (SHM) applied to acoustic tubes. This system emerges as an alternative to traditional inspection methodologies in mechanical structures providing high efficiency combined with speed and monetary savings. This system has the ability to assess the remaining life of the structure and assist in decision-making, being able to intervene in situations of critical stress, preserving lives and the long-term functioning of the structure. The objective is the theoretical basis and the detection of failures in pipes by acoustic means. The Clonal Selection Algorithm is based on the continuous learning capacity of the biological immune system, having the ability to learn by repetition and memory. This method requires less training data than is usually used in the literature, with approximately 71% less data. The results presented showed how it is possible and effective to detect failure with a 100% accuracy.
Type of Study: Research paper |
Subject:
General
References
1. G. L. Ada, S. G. Nossal, The Clonal-Selection Theory, Scientific American, 257(2), (1987), 62-69. [DOI:10.1038/scientificamerican0887-62]
2. D. Balageas, C. P. Fritzen, A. G¨uemes, Structural Health Monitoring, John Wiley & Sons, 2010.
3. D. W. Bradley, A. M. Tyrrell, Immunotronics-Novel Finite-State-Machine Architectures with Built-in Self-Test Using Self-Nonself Differentiation, IEEE Transactions on Evolutionary Computation, 6(3), (2002), 227-238. [DOI:10.1109/TEVC.2002.1011538]
4. L. N. Castro, L. N. de Castro, J. Timmis, Artificial Immune Systems: A New Computational Intelligence Approach, Springer Science & Business Media, 2002.
5. D. Dasgupta, F. Nino, Immunological Computation: Theory and Applications, CRC press, 2008. [DOI:10.1201/9781420065466]
6. L. N. de Castro, Engenharia Imunol'ogica: Desenvolvimento e Aplica¸c˜ao de Ferramentas Computacionais Inspiradas em Sistemas Imunol'ogicos Artificiais, Universidade Estadual de Campinas, Campinas-SP, 2001.
7. L. N. de Castro, F. J. Von Zuben, The Clonal Selection Algorithm With Engineering Applications, Proceedings of GECCO, (2000), 36-39.
8. S. W. Doebling, C. R. Farrar, M. B. Prime, A Summary Review of Vibration-Based Damage Identification Methods, Shock and vibration digest, Washington, DC: The Center, 30(2), (1998), 91-105. [DOI:10.1177/058310249803000201]
9. S. Forrest, A. S. Perelson, L. Allen, R. Cherukuri, Self-Nonself Discrimination in a Computer, Proceedings of 1994 IEEE computer society symposium on research in security and privacy, 1999, 202-212. [DOI:10.1109/RISP.1994.296580]
10. V. R. Franco, D. D. Bueno, M. J. Brennan, A. A. Cavalini Jr, C. G. Gonsalez, V. Lopes Jr, Experimental Damage Location in Smart Structures Using Lamb Waves Approaches, Brazilian Conference on Dynamics, Control and Their Applications-DINCON, (2009),1-4.
11. A. Gaffar, A. B. Joshi, S. Singh, V. N. Mishra, H. G. Rosales, L. Zhou, A. Dhaka, L. N. Mishra, A Technique for Securing Multiple Digital Images Based on 2D Linear Congruential Generator, Silver Ratio, and Galois Field, IEEE Access, 9, (2021), 96125-96150. DOI: 10.1109/ACCESS.2021.3094129. [DOI:10.1109/ACCESS.2021.3094129]
12. S. N. Y. Gerges, Ru'ıdo: Fundamentos e Controle, Florianopolis: NR Editora, 2000, 696.
13. S. Gopalakrishnan, M. Ruzzene, S. Hanagud, Computational Techniques for Structural Health Monitoring, Springer Science & Business Media, 2011. [DOI:10.1007/978-0-85729-284-1]
14. S. R. Hall, The Effective Management and Use of Structural Health Data, Proceedings of the 2nd International Workshop on Structural Health Monitoring, 1999, 265-275.
15. S. P. Jakhar, A. Nandal, A. Dhaka, B. Jiang, L. Zhou, V.N. Mishra, Fractal Feature Based Image Resolution Enhancement Using Wavelet-Fractal Transformation in Gradient Domain, Journal of Circuits, Systems and Computers, 32(2), (2023), DOI:
https://doi.org/10.1142/S0218126623500354 [DOI:10.1142/S0218126623500354.]
16. G. James, D. Witten, T. Hastie, R. Tibshirani, An Introduction to Statistical Learning, Springer, 112, 2013. [DOI:10.1007/978-1-4614-7138-7]
17. L. E. Kinsler, A. R. Frey, A. B. Coppens, J. V. Sanders, Fundamentals of Acoustics, Fundamentals of Acoustics, 4th Edition, Wiley-VCH, 1999, 560.
18. F. P. A. Lima, An'alise de Dist'urbios de Tens˜ao em Sistemas de Distribui¸c˜ao de Energia El'etrica Baseada em Sistemas Imunol'ogicos Artificiais, Universidade Estadual Paulista (UNESP), 2013.
19. F. P. A. Lima, Monitoramento e Identifica¸c˜ao de Falhas em Estruturas Aeron'auticas e Mecˆanicas Utilizando T'ecnicas de Computa¸c˜ao Inteligente, Universidade Estadual Paulista (UNESP), 2014.
20. F. P. A. Lima, Diagn'ostico de Dist'urbios de Tens˜ao em Sistemas de Distribui¸c˜ao Baseado num Sistema Imunol'ogico Artificial com Aprendizado Continuado, Universidade Estadual Paulista (UNESP), 2016.
21. R. Lanoye, G. Vermeir, W. Lauriks, R. Kruse, V. Mellert, Measuring The Free Field Acoustic Impedance and Absorption Coefficient of Sound Absorbing Materials With a Combined Particle Velocity-Pressure Sensor, The Journal of the Acoustical Society of America, 119(5), (2006), 2826-2831. [DOI:10.1121/1.2188821]
22. F. P. A. Lima, F. R. Chavarette, S. S. F. Souza, M. L. M Lopes, Monitoring and fault identification in Aeronautical Structures Using an Wavelet-Artificial Immune System Algorithm, Probabilistic Prognostics and Health Management of Energy Systems, Springer, (2007), 203-219.
23. F. P. A. Lima, F. R. Chavarette, S. S. F. Souza, A. S. Souza, M. L. M. Lopes, Artificial Immune Systems Applied to the Analysis of Structural Integrity of a Building, Applied Mechanics and Materials, 472, (2014), 544-549. [DOI:10.4028/www.scientific.net/AMM.472.544]
24. F. P. A. Lima, M. L. M. Lopes, A. D. P. Lotufo, C. R. Minussi, An Artificial Immune System With Continuous-Learning for Voltage Disturbance Diagnosis in Electrical Distribution Systems, Expert systems with applications, 56, (2016), 131-142. [DOI:10.1016/j.eswa.2016.03.010]
25. I. F. Merizio, F. R. Chavarette, R. Outa, Characterization of an Acoustic Impedance Tube Using Natural Computer, Colloquium Exactarum, 11(4), (2019), 62-72. [DOI:10.5747/ce.2019.v11.n4.e297]
26. D. C. Oliveira, F. R. Chavarette, F. P. A. Lima, Structural Health Monitoring using Artificial Immune System, Brazilian Journal of Development, 6(4), (2020), 16948-16963. [DOI:10.34117/bjdv6n4-022]
27. D. C. Oliveira, F. R. Chavarette, M. L. M. Lopes, Damage Diagnosis in an IsotropicStructure Using an Artificial Immune System Algorithm, Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41(11), (2019), 485-492. [DOI:10.1007/s40430-019-1971-9]
28. R. Outa, F. R. Chavarette, Caracteriza¸c˜ao do Experimento do Tubo de Impedˆancia de um Microfone, Boletim Tecnico da FATEC-SP - BT/39 - Junho, 2015.
29. R. Outa, F. R. Chavarette, V. N. Mishra, A. C. Gon¸calves, L. G. P. Roefero, T. C. Moro, Prognosis and Fail Detection in a Dynamic Rotor Using Artificial Immunological System, Engineering Computations 37(9), (2020), 3127-3145. [DOI:10.1108/EC-08-2019-0351]
30. M. K. Sharma, Sadhna, A. K. Bhargava, S. Kumar, L. Rathour, L. N. Mishra, S. Pandey, A Fermatean Fuzzy Ranking Function in Optimization of Intuitionistic Fuzzy Transportation Problems, Advanced Mathematical Models & Applications, 7(2), (2022), 191-204.
31. S. L. Wiggers, P. Pedersen, Structural Stability and Vibration: An Integrated Introduction by Analytical and Numerical Methods, Springer, 2018. [DOI:10.1007/978-3-319-72721-9_16]
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
