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Erschienen in:
2023 | OriginalPaper | Buchkapitel
Damage Detection in Rods via Use of a Genetic Algorithm and a Deep-Learning Based Surrogate
verfasst von : Jitendra K. Sharma, Rohan Soman, Pawel Kudela, Eleni Chatzi, Wieslaw Ostachowicz
Erschienen in: European Workshop on Structural Health Monitoring
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Abstract
This research demonstrates the use of genetic algorithms for damage detection in isotropic rods. The spectral element method and a deep-learning-based surrogate model is utilized for simulating wave propagation in an isotropic cracked rod. The genetic algorithm employs results (“numerical experiment") obtained from the spectral element model and the deep-learning-based surrogate to determine the optimized crack locations and crack depths as output parameters. The objective function used in the genetic algorithm is the mean square error between the response obtained from spectral element model and the deep-learning-based surrogate model.