A MODWT-Based Algorithm for the Identification and Removal of Jumps/Short-Term Distortions in Displacement Measurements Used for Structural Health Monitoring

Davi V. Q. Rodrigues, D. Zuo, Changzhi Li
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引用次数: 3

Abstract

Researchers have made substantial efforts to improve the measurement of structural reciprocal motion using radars in the last years. However, the signal-to-noise ratio of the radar’s received signal still plays an important role for long-term monitoring of structures that are susceptible to excessive vibration. Although the prolonged monitoring of structural deflections may provide paramount information for the assessment of structural condition, most of the existing structural health monitoring (SHM) works did not consider the challenges to handle long-term displacement measurements when the signal-to-noise ratio of the measurement is low. This may cause discontinuities in the detected reciprocal motion and can result in wrong assessments during the data analyses. This paper introduces a novel approach that uses a wavelet-based multi-resolution analysis to correct short-term distortions in the calculated displacements even when previously proposed denoising techniques are not effective. Experimental results are presented to validate and demonstrate the feasibility of the proposed algorithm. The advantages and limitations of the proposed approach are also discussed.
基于modwt的结构健康监测位移测量中跳跃/短期畸变识别和去除算法
在过去的几年里,研究人员已经做出了大量的努力来改进使用雷达测量结构往复运动。然而,雷达接收信号的信噪比对于易受过度振动影响的结构的长期监测仍然起着重要的作用。虽然长时间的结构位移监测可以为结构状态评估提供重要的信息,但大多数现有的结构健康监测(SHM)工作没有考虑到在测量信噪比较低的情况下处理长期位移测量的挑战。这可能会导致检测到的相互运动不连续性,并可能导致数据分析期间的错误评估。本文介绍了一种新颖的方法,该方法使用基于小波的多分辨率分析来校正计算位移中的短期畸变,即使以前提出的去噪技术无效。实验结果验证了该算法的可行性。本文还讨论了该方法的优点和局限性。
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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