首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >Sparse Wavenumber Recovery and Prediction of Anisotropic Guided Waves in Composites: A Comparative Study
【24h】

Sparse Wavenumber Recovery and Prediction of Anisotropic Guided Waves in Composites: A Comparative Study

机译:复合材料中各向异性导波的稀疏波数恢复和预测:比较研究

获取原文
获取原文并翻译 | 示例
           

摘要

Guided wave methodologies are among the established approaches for structural health monitoring (SHM). For guided wave data, being able to accurately estimate wave properties in the absence of ample measurements can greatly facilitate the often time-consuming and potentially expensive data acquisition procedure. Nevertheless, inherent complexities of the guided waves, including their multimodal and frequency dispersive nature, hinder processing, analysis, and behavior prediction. The severity of these complexities is even higher in anisotropic media, such as composites. Several methods, including sparse wavenumber analysis (SWA), have been proposed in the literature to characterize guided wave propagation by extracting wave characteristics in a particular medium from the information contained in a few measurements, and subsequently using this information for full wavefield prediction. In this paper, we investigate the efficacy of guided wave reconstruction techniques, based on SWA, for predicting the behavior of guided waves in composite materials. We implement these techniques on several experimental and simulation data sets. We study their performance in estimating the frequency-dependent (dispersive) and anisotropic velocities of guided waves and in reconstructing full wavefields from limited available information.
机译:导波方法论是结构健康监测(SHM)的既定方法之一。对于导波数据,在没有足够的测量值的情况下能够准确估计波的属性可以极大地简化通常耗时且可能昂贵的数据采集过程。然而,导波固有的复杂性,包括其多峰和频率色散特性,阻碍了处理,分析和行为预测。这些复杂性的严重性在各向异性介质(例如复合材料)中甚至更高。文献中已经提出了几种方法,包括稀疏波数分析(SWA),通过从几次测量中包含的信息中提取特定介质中的波特征,然后将这些信息用于全波场预测来表征导波传播。在本文中,我们研究了基于SWA的导波重建技术在预测复合材料中导波行为方面的功效。我们在几个实验和模拟数据集上实施这些技术。我们研究了它们在估计导波的频率相关(色散)和各向异性速度以及从有限的可用信息重建全波场方面的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号