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Correlative sensor array and its applications to identification of damage in plate-like structures

机译:相关传感器阵列及其在板状结构损伤识别中的应用

摘要

Lamb waves, the guided elastic waves in thin plate/shell structures, have been the core of intensive research for developing cost-effective damage identification techniques over decades. In this regard, appropriate and optimal allocation of actuators and sensors in a sensor array/network is a pivotal concern for achieving sufficient information to describe the damage and meanwhile for minimising interferences of multiple wave modes and complex wave reflection from structural boundaries. An active sensor array comprising a number of miniaturised piezoelectric wafers aligned strategically was developed in the study, named correlative sensor array (CSA) to reflect its mechanism based on signal correlation processing. Using the time differences of different Lamb waves captured by individual array members, a CSA is able to facilitate awareness of structural damage and subsequently to locate it. To ascertain time difference accurately, a signal processing algorithm capitalising on signal correlation and moving-window-based likelihood searching was integrated with the array. The CSA with integrated signal processing algorithm was then numerically and experimentally applied to the identification of a through-thickness hole in an aluminium plate, and the identification results have shown the feasibility and effectiveness of the CSA for pinpointing damage in plate-like structures. As supplement, limitations of CSA-based damage detection in terms of the effective detection area and sensitivity were explored.
机译:几十年来,作为薄板/壳结构中的引导弹性波的兰姆波一直是开发具有成本效益的损伤识别技术的深入研究的核心。在这方面,传感器阵列/网络中致动器和传感器的适当和最佳分配是获得足够的信息来描述损坏并同时最小化多波模式的干扰和结构边界的复杂波反射的关键问题。在这项研究中,开发了一种有源传感器阵列,该阵列包括多个经过战略性排列的小型压电晶片,称为相关传感器阵列(CSA),以反映基于信号相关处理的机制。利用单个阵列成员捕获的不同兰姆波的时差,CSA能够促进对结构破坏的认识并随后对其进行定位。为了准确地确定时间差,将利用信号相关性和基于移动窗口的似然搜索的信号处理算法与阵列集成在一起。然后,将具有集成信号处理算法的CSA数值和实验应用于铝板中厚板通孔的识别,识别结果表明了CSA精确定位板状结构中的损伤的可行性和有效性。作为补充,探讨了基于CSA的损坏检测在有效检测区域和灵敏度方面的局限性。

著录项

  • 作者

    Yu L; Cheng L; Su Z;

  • 作者单位
  • 年度 2012
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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