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Aircraft Structural Integrity Assessment through Computational Intelligence Techniques

RamanaM. Pidaparti1

1 Department of Mechanical Engineering, Virginia Commonwealth University, Richmond, VA 23284. E-mail: rmpidaparti@vcu.edu

Structural Durability & Health Monitoring 2006, 2(3), 131-148. https://doi.org/10.3970/sdhm.2006.002.131

Abstract

This paper provides an overview of the computational intelligence methods developed for the structural integrity assessment of aging aircraft structures. Computational intelligence techniques reviewed include artificial neural networks, inverse neural network mapping, wavelet based image processing methods, genetic algorithms, spectral element methods, and particle swarm optimization. Multi-site damage, corrosion, and corrosion-fatigue damage in aging aircraft is specifically discussed. Results obtained from selected computational intelligence methods are presented and compared to the existing alternate solutions and experimental data. The results presented illustrate the applicability of computational intelligence methods for assessing the structural integrity of aging aircraft structures and materials.

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Cite This Article

APA Style
Pidaparti, R. (2006). Aircraft structural integrity assessment through computational intelligence techniques. Structural Durability & Health Monitoring, 2(3), 131-148. https://doi.org/10.3970/sdhm.2006.002.131
Vancouver Style
Pidaparti R. Aircraft structural integrity assessment through computational intelligence techniques. Structural Durability Health Monit . 2006;2(3):131-148 https://doi.org/10.3970/sdhm.2006.002.131
IEEE Style
R. Pidaparti, "Aircraft Structural Integrity Assessment through Computational Intelligence Techniques," Structural Durability Health Monit. , vol. 2, no. 3, pp. 131-148. 2006. https://doi.org/10.3970/sdhm.2006.002.131



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