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http://dx.doi.org/10.7734/COSEIK.2020.33.6.359

Simulation-Based Damage Estimation of Helideck Using Artificial Neural Network  

Kim, Chanyeong (Department of Ocean Engineering, Korea Maritime and Ocean Univ.)
Ha, Seung-Hyun (Department of Ocean Engineering, Korea Maritime and Ocean Univ.)
Publication Information
Journal of the Computational Structural Engineering Institute of Korea / v.33, no.6, 2020 , pp. 359-366 More about this Journal
Abstract
In this study, a simulation-based damage estimation method for helidecks is proposed using an artificial neural network. The structural members that share a connecting node in the helideck are regarded as a damage group, and a total of 37,400 damage scenarios are numerically generated by applying randomly assigned damage to up to three damage groups. Modal analysis is then performed for all the damage scenarios, which are selectively used as either training or validation or verification sets based on the purpose of use. An artificial neural network with three hidden layers is constructed using a PyTorch program to recognize the patterns of the modal responses of the helideck model under both damaged and undamaged states, and the network is successively trained to minimize the loss function. Finally, the estimated damage rate from the proposed artificial neural network is compared to the actual assigned damage rate using 400 verification scenarios to show that the neural network is able to estimate the location and amount of structural damage precisely.
Keywords
artificial neural network; damage estimation; helideck; modal analysis; pattern recognition;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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