基于SHM方法的Lamb波拓扑分析

IF 5.7 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Arthur Lejeune, Nicolas Hascoët, Marc Rébillat, Eric Monteiro, Nazih Mechbal
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引用次数: 0

摘要

拓扑数据分析(TDA)是一种强大而有前途的数据分析工具,但尚未得到充分利用。它是一种多维度的方法,可以提取给定数据集中包含的拓扑特征。本文介绍了一种原始的基于tda的方法,该方法允许在安装压电换能器(PZTs)时监测结构的健康状况。利用基于Lamb波的结构健康监测(SHM)方法,通过对测量时间序列数据进行特定的预处理,可以大大提高TDA(持续同源性)的损伤检测和分类能力。TDA工具首先以传统方式直接应用,以便使用同源类来评估损害。在此基础上,提出了另一种基于时间数据切片的方法,以提高持久性同源性感知,并利用拓扑描述符区分不同的损伤。用于应用这两种方法的数据集来自于对嵌入pzt的航空复合材料板进行的实验活动,其中研究了不同的损伤类型,如分层、冲击和刚度降低。所提出的方法能够考虑先验的物理信息,并提供了一种比传统的TDA方法更好的损害分类方法。综上所述,本文证明了使用TDA对PZTs时间序列信号的拓扑特征进行处理提供了一种有效的方法来分离和分类损伤性质,并为TDA在SHM中的进一步发展开辟了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An enhanced topological analysis for Lamb waves based SHM methods
Topological data analysis (TDA) is a powerful and promising tool for data analysis, but yet not exploited enough. It is a multidimensional method which can extract the topological features contained in a given dataset. An original TDA-based method allowing to monitor the health of structures when equipped with piezoelectric transducers (PZTs) is introduced here. Using a Lamb wave based Structural Health Monitoring (SHM) approach, it is shown that with specific pre-processing of the measured time-series data, the TDA (persistent homology) for damage detection and classification can be greatly improved. The TDA tool is first applied directly in a traditional manner in order to use homology classes to assess damage. After that, another method based on slicing the temporal data is developed to improve the persistence homology perception and to leverage topological descriptors to discriminate different damages. The dataset used to apply both methods comes from experimental campaigns performed on aeronautical composite plates with embedded PZTs where different damage types have been investigated such as delamination, impacts and stiffness reduction. The proposed approach enables to consider a priori physical information and provides a better way to classify damages than the traditional TDA approach. In summary, this article demonstrates that manipulating the topological the features of PZTs time-series signals using TDA provides an efficient mean to separate and classify the damage natures and opens the way for further developments on the use of TDA in SHM.
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来源期刊
CiteScore
12.80
自引率
12.10%
发文量
181
审稿时长
4.8 months
期刊介绍: Structural Health Monitoring is an international peer reviewed journal that publishes the highest quality original research that contain theoretical, analytical, and experimental investigations that advance the body of knowledge and its application in the discipline of structural health monitoring.
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