Structural Health Monitoring using Artificial Immune System / Monitoramento estrutural da saúde usando sistema imunológico artificial

Daniela Cabral de Oliveira, Fábio Roberto Chavarette, Fernando Parra dos Anjos Lima

Abstract


This work proposes intelligent computer techniques which aims to detect structural damages in aircraft using the artificial immune system technique with negative selection and clonal selection. This concept results in a diagnosis system that is able to learn continuously, comprising different damage situations, without needing to restart the learning process. Considering this, two artificial immune systems were employed, the first of which, the negative selection algorithm, is responsible for pattern recognition, and second one, the clonal selection algorithm, is responsible for the continuous learning process. The experiment was prepared using piezoelectric transducers attached to an aluminum plate (representing an airplane wing), which act both as sensors and actuators, and signals that represent baseline and damage conditions were acquired. The results show that the proposed methodology is robust and accurate.

 


Keywords


Structural health monitoring, Isotropic structures, Artificial immune systems, Negative selection algorithm, Clonal selection algorithm.

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References


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DOI: https://doi.org/10.34117/bjdv6n4-022

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