Generated datasets from dynamic reproduction of projectiles in ballistic environments for advanced research (DROPBEAR) testbed

Matthew Nelson, S. Laflamme, Chao Hu, A. Moura, Jonathan Hong, Austin Downey, P. Lander, Yang Wang, Erik Blasch, J. Dodson
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引用次数: 2

Abstract

High-rate dynamics occur when a system’s acceleration is larger than 100 gn over durations less than 100 ms. Structural health monitoring algorithms must be created for high-rate dynamic systems to maximize safety and minimize economic losses. There is a need to evaluate these algorithms for precision and accuracy prior to real-world implementation. An experimental testbed was created to simulate large-magnitude events while maintaining repeatability to accurately and robustly assess various structural health monitoring algorithms’ capability to monitor high-rate dynamic systems. All previous datasets created on the experimental testbed are discussed, examining various sensor setups, excitations, and boundary condition changes to properly simulate near-high-rate events and provide robust experimental data to evaluate structural health monitoring algorithms.
为高级研究(DROPBEAR)试验台从弹道环境中弹丸的动态再现生成数据集
当系统加速度大于100gn,持续时间小于100ms时,就会出现高速率动力学。为了使高速率动态系统的安全性最大化和经济损失最小化,必须创建结构健康监测算法。在现实世界实现之前,需要评估这些算法的精度和准确性。建立了一个实验测试平台来模拟大震级事件,同时保持可重复性,以准确、稳健地评估各种结构健康监测算法监测高速率动态系统的能力。讨论了之前在实验测试台上创建的所有数据集,检查了各种传感器设置、激励和边界条件变化,以正确模拟近高速率事件,并提供可靠的实验数据来评估结构健康监测算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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