关于纤维布拉格格感应器应力曲线聚类算法的研究
Yisen Lin1, Ye Wang2, Huichen Qu1
1School of Computer Science and Engineering, Guilin University of Aerospace Technology, Guilin, 541004, China.
Scientific reports
|July 21, 2023
概括
这项研究引入了一种新的压力曲线聚类算法,用于纤维布拉格格子传感器,以改善建筑健康监测. 新方法提高了分类日常压力负载的准确性,有助于结构健康评估.
科学领域:
- 结构工程 结构工程
- 传感器技术 传感器技术
- 数据科学数据科学数据科学
背景情况:
- 在线结构健康评估需要准确分析建筑压力分布.
- 纤维布拉格格 (FBG) 传感器产生复杂的应力曲线数据.
- 现有的集群算法面临着高维和稀疏传感器数据的挑战.
研究的目的:
- 为FBG传感器开发一个有效的应力曲线集群算法.
- 提高分类日常应力负载特征的准确性和效率.
- 为先进的建筑结构健康分析模型提供基础.
主要方法:
- 为FBG应力传感器数据提出了一种密度聚类算法.
- 利用改进的共弦相似度来测量高维空间中的样本距离.
- 为了高效的分类,采用了基于最近邻居的密度聚类方法.
主要成果:
- 成功分类了FBG传感器的每日应力负载特征.
- 与最先进的算法 (HDBSCAN,CBKM,K-mean++,FINCH,NPIR) 相比,表现出更高的性能.
- 验证了算法适用于FBG传感器应力曲线特征分类的适用性.
结论:
- 开发的应力曲线集群算法有效地分析FBG传感器数据.
- 这种方法为结构健康监测应用提供了显著的改进.
- 应力负荷特征的分类为构建健康数学模型提供了基础.
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