Artificial Immune Systems with Negative Selection Applied to Health Monitoring of Aeronautical Structures

Abstract:

In this paper we present a system for aircraft structural health monitoring based on artificial immune systems with negative selection. Inspired by a biological process, the principle of discrimination proper/non-proper, identifies and characterizes the signs of structural failure. The main application of this method is to assist in the inspection of aircraft structures, to detect and characterize flaws and decision making in order to avoid disasters. We proposed a model of an aluminum beam to perform the tests of the method. The results obtained by this method are excellent, showing robustness and accuracy.

• Periodical: Advanced Materials Research (Volume 871)
• Pages: 283-289
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.871.283
• Online since: December 2013
• Authors: Fernando Parra dos Anjos Lima, Fábio Roberto Chavarette, Adriano dos Santos e Souza, Simone Silva Frutuoso de Souza, Mara Lúcia Martins Lopes
• Keywords: Aeronautical Structures, Artificial Immune Systems, Health Monitoring, Negative Selection Algorithm

References

[1] D. W. Bradley and A. M. Tyrrell. Immunotronics - Novel Finite-State-Machine Architectures with Built-In Self-Test Using Self-Nonself Differentiation. IEEE Transactions on Evolutionary Computation. Vol. 6, p.227–238 (2002).

DOI: 10.1109/tevc.2002.1011538

[2] M. Chandrashekhar; R. Ganguli. Structural damage detection using modal curvature and fuzzy logic. Structural Health Monitoring, USA, v. 8, n. 4, pp.267-282, (2009).

DOI: 10.1177/1475921708102088

[3] D. Dasgupta. Artficial Immune Systems and Their Applications,. Springer-Verlag New York, Inc., Secaucus, NJ, USA, (1998).

[4] L. N. de Castro and J. TIMMIS. Artificial Immune Systems: A New Computational Intelligence Approach, Springer. 1st edition, (2002).

[5] S. Forrest; A. Perelson; L. Allen and R. Cherukuri. Self-Nonself Discrimination in a computer, Proc. do IEEE Symposium on Research in Security and Privacy, pp.202-212 (1994).

DOI: 10.1109/risp.1994.296580

[6] 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. In: Brazilian Conference on Dynamics, Control and Their Applications – DINCON. pp.1-4. (2009).

[7] V. Giurgiutiu. Tuned lamb wave excitation and detection with piezoelectric wafer active sensors for structural health monitoring. Journal of Intelligent Material Systems and Structures, USA, v. 16, n. 4, p.291–305, (2005).

DOI: 10.1177/1045389x05050106

[8] S. R. Hall. The effective management and use of structural health data. In: International Workshop on Structural Health Monitoring, pp.265-275. (1999).

[9] M. Krawczuk; W. Ostachowicz; G. Kawiecki. Detection of delaminations in cantilevered beams using soft computing methods. In: Conference on System Identification and Structural Health Monitoring, Madrid, p.243–252 (2000).

[10] F. P. A. Lima; A. D. P. Lotufo and C. R. Minussi. Artificial Immune Systems Applied to Voltage Disturbance Diagnosis in Distribution Electrical Systems, Proceedings on IEEE PowerTech-2013, Grenoble, France, 6 p (2013).

DOI: 10.1109/ptc.2013.6652127

[11] Matlab (2011). 7. 8 Version, Mathworks Company.

[12] T. Shen; F. Wan; B. Song; Y. Wu. Damage Location and Identification of the Wing Structure With probabilistic neural Networks. Prognostics & System Health Management Conference (PHM 2011). p.1–6, (2011).

DOI: 10.1109/phm.2011.5939524

[13] C. Xiang-Jun; G. Zhan-Feng; G. Qiang. Application of wavelet analysis in vibration signal processing of bridge structure. International Conference on Measuring Technology and Mechatronics Automation. p.671–674, (2010).

DOI: 10.1109/icmtma.2010.95

[14] S. Zheng; X. Wang; L. Liu. Damage detection in composite materials based upon the computational mechanics and neural networks. In: European Workshop on Structural Health Monitoring, Munich, p.609–615 (2004).

[15] F. L. Wang; T. H. T. Chan; D. P. Thambiratnam and A. C. C. Tan. Damage Diagnosis for Complex Steel Truss Bridges Using Multi-Layer Genetic Algorithm. Journal of Civil structural Health Monitoring, Springer-Verlag, p.117–217, (2013).

DOI: 10.1007/s13349-013-0041-8