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基于原位雷达和超声波测量的结构木材成像:现状综述

Imaging of Structural Timber Based on In Situ Radar and Ultrasonic Wave Measurements: A Review of the State-of-the-Art.

作者信息

Pahnabi Narges, Schumacher Thomas, Sinha Arijit

机构信息

Civil and Environmental Engineering, Portland State University, Portland, OR 97201, USA.

Wood Science and Engineering, Oregon State University, Corvallis, OR 97331, USA.

出版信息

Sensors (Basel). 2024 May 1;24(9):2901. doi: 10.3390/s24092901.

Abstract

With the rapidly growing interest in using structural timber, a need exists to inspect and assess these structures using non-destructive testing (NDT). This review article summarizes NDT methods for wood inspection. After an overview of the most important NDT methods currently used, a detailed review of Ground Penetrating Radar (GPR) and Ultrasonic Testing (UST) is presented. These two techniques can be applied in situ and produce useful visual representations for quantitative assessments and damage detection. With its commercial availability and portability, GPR can help rapidly identify critical features such as moisture, voids, and metal connectors in wood structures. UST, which effectively detects deep cracks, delaminations, and variations in ultrasonic wave velocity related to moisture content, complements GPR's capabilities. The non-destructive nature of both techniques preserves the structural integrity of timber, enabling thorough assessments without compromising integrity and durability. Techniques such as the Synthetic Aperture Focusing Technique (SAFT) and Total Focusing Method (TFM) allow for reconstructing images that an inspector can readily interpret for quantitative assessment. The development of new sensors, instruments, and analysis techniques has continued to improve the application of GPR and UST on wood. However, due to the hon-homogeneous anisotropic properties of this complex material, challenges remain to quantify defects and characterize inclusions reliably and accurately. By integrating advanced imaging algorithms that consider the material's complex properties, combining measurements with simulations, and employing machine learning techniques, the implementation and application of GPR and UST imaging and damage detection for wood structures can be further advanced.

摘要

随着对使用结构木材的兴趣迅速增长,需要使用无损检测(NDT)对这些结构进行检查和评估。这篇综述文章总结了用于木材检测的无损检测方法。在概述了目前使用的最重要的无损检测方法之后,对探地雷达(GPR)和超声检测(UST)进行了详细综述。这两种技术可以现场应用,并能生成用于定量评估和损伤检测的有用可视化图像。由于其商业可用性和便携性,探地雷达有助于快速识别木结构中的关键特征,如湿度、空隙和金属连接件。超声检测能有效检测深层裂缝、分层以及与含水量相关的超声波速度变化,可补充探地雷达的功能。这两种技术的无损特性保持了木材的结构完整性,能够在不损害完整性和耐久性的情况下进行全面评估。合成孔径聚焦技术(SAFT)和全聚焦方法(TFM)等技术可以重建图像,便于检测人员进行定量评估。新传感器、仪器和分析技术的发展不断改进了探地雷达和超声检测在木材上的应用。然而,由于这种复杂材料的非均匀各向异性特性,在可靠、准确地量化缺陷和表征内含物方面仍然存在挑战。通过整合考虑材料复杂特性的先进成像算法、将测量与模拟相结合以及采用机器学习技术,可以进一步推进探地雷达和超声检测成像以及木结构损伤检测的实施和应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab66/11086303/f472b93f3c99/sensors-24-02901-g0A1.jpg

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