形状感知算法的关键比较:校准矩阵方法与iFEM相比
Cornelis de Mooij1, Marcias Martinez2
1Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, 2629 HS Delft, The Netherlands.
Sensors (Basel, Switzerland)
|June 19, 2024
概括
校准矩阵 (CM) 方法在形状感应准确性和用于重建位移和应变的计算效率方面明显优于反向有限元素方法 (iFEM). CM实现了<0.01%的误差,而iFEM的误差高达99%.
科学领域:
- 结构健康监测 结构健康监测
- 计算力学 计算力学 计算力学
- 航空航天工程 航空航天工程
背景情况:
- 精确的结构位移和应变的重建对于负载监测至关重要,特别是对于离散和不规则分布的传感器数据.
- 现有的形状感知算法,如校准矩阵 (CM) 方法和反向有限元素方法 (iFEM),对变形重建有不同的方法.
研究的目的:
- 为了比较CM方法和iFEM用于形状传感的准确性和计算效率.
- 评估CM方法的适用性和实用性,用于从传感器数据中重建完整的位移和应变场.
主要方法:
- 校准矩阵 (CM) 方法使用已知负载情况和测量传感器数据的线性组合重建变形.
- 反向有限元法 (iFEM) 通过最小化测量值和数值之间的最小平方误差来重建变形.
- 这两种方法都应用于基准问题和代表性航空航天结构 (扭曲,缩的刀片) 使用正方形六面体固体元素.
主要成果:
- CM方法的准确性显著提高,平均位移和张力误差低于0.01%.
- 相比之下,iFEM算法的平均位移和应变误差分别为21%和99%.
- 对于大型传感器数量,CM表现出同等或更高的计算效率,重复解决时间大约比iFEM快100倍.
结论:
- CM方法是一种高度准确和计算效率高的形状传感算法,特别适用于带有离散传感器数据的负载监控应用.
- 在准确性和速度方面,CM的卓越性能使其成为复杂结构分析中比iFEM更实用和有利的选择.
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