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使用超声导波的大型金属结构的结构健康监测(SHM)和表面缺陷测定。

Structural Health Monitoring (SHM) and Determination of Surface Defects in Large Metallic Structures using Ultrasonic Guided Waves.

机构信息

Department of Energy and Power, Cranfield University, Bedfordshire MK43 0AL, UK.

出版信息

Sensors (Basel). 2018 Nov 15;18(11):3958. doi: 10.3390/s18113958.

Abstract

Ultrasonic guided wave (UGW) is one of the most commonly used technologies for non-destructive evaluation (NDE) and structural health monitoring (SHM) of structural components. Because of its excellent long-range diagnostic capability, this method is effective in detecting cracks, material loss, and fatigue-based defects in isotropic and anisotropic structures. The shape and orientation of structural defects are critical parameters during the investigation of crack propagation, assessment of damage severity, and prediction of remaining useful life (RUL) of structures. These parameters become even more important in cases where the crack intensity is associated with the safety of men, environment, and material, such as ship's hull, aero-structures, rail tracks and subsea pipelines. This paper reviews the research literature on UGWs and their application in defect diagnosis and health monitoring of metallic structures. It has been observed that no significant research work has been convened to identify the shape and orientation of defects in plate-like structures. We also propose an experimental research work assisted by numerical simulations to investigate the response of UGWs upon interaction with cracks in different shapes and orientations. A framework for an empirical model may be considered to determine these structural flaws.

摘要

超声导波(UGW)是用于结构部件的无损评估(NDE)和结构健康监测(SHM)的最常用技术之一。由于其出色的远程诊断能力,该方法可有效检测各向同性和各向异性结构中的裂纹、材料损失和基于疲劳的缺陷。在研究裂纹扩展、评估损伤严重程度和预测结构的剩余使用寿命(RUL)时,结构缺陷的形状和方向是关键参数。在与人员安全、环境和材料(如船体、航空结构、轨道和海底管道)相关的裂纹强度的情况下,这些参数变得更加重要。本文回顾了关于 UGW 及其在金属结构缺陷诊断和健康监测中应用的研究文献。已经观察到,没有进行大量研究工作来识别板状结构中缺陷的形状和方向。我们还提出了一项实验研究工作,通过数值模拟研究 UGW 在与不同形状和方向的裂纹相互作用时的响应。可以考虑建立一个经验模型框架来确定这些结构缺陷。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/026d/6263499/23a8ad514f71/sensors-18-03958-g001.jpg

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