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用于检测和测量混凝土中嵌入式圆柱形物体的超声透射层析成像

Ultrasound Transmission Tomography for Detecting and Measuring Cylindrical Objects Embedded in Concrete.

作者信息

Lluveras Núñez Dalmay, Molero-Armenta Miguel Ángel, Izquierdo Miguel Ángel García, Hernández Margarita González, Anaya Velayos José Javier

机构信息

Instituto de Tecnologías Físicas y de la Información, ITEFI (CSIC), C/Serrano 144, 28006 Madrid, Spain.

Innerspec Technologies Europe, Av. Madrid km. 27.2, 28802 Alcalá de Henares, Spain.

出版信息

Sensors (Basel). 2017 May 10;17(5):1085. doi: 10.3390/s17051085.

Abstract

This study explores the feasibility of using transmission tomographic images based on attenuation measures in transmission to detect and estimate the most common materials that are embedded in concrete, reinforcements and natural and artificial voids. A limited set of concrete specimens have been made in which cylindrical objects such as bars/tubes of steel, PVC and aluminium have been embedded to analyse the effect of size and material. The methodology and scope of this study is presented and numerical simulations are carried out to optimize the emitter-receiver configuration and to understand the complex physical propagation phenomena of ultrasonic signals that travel through concrete with embedded inclusions. Experimental tomographic images are obtained by using an ultrasonic tomographic system, which has the advantage of needing only two ultrasonic transducers. Both the software simulation tool and the tomographic inspection system are developed by the authors. The obtained results show that PVC tubes and steel bars of diameters higher than 19 mm and embedded in cylindrical specimens, can be detected and their sizes estimated using segmented tomographic images.

摘要

本研究探讨了利用基于透射衰减测量的透射层析图像来检测和估计混凝土、钢筋以及天然和人工孔洞中最常见嵌入材料的可行性。制作了一组有限的混凝土试件,其中嵌入了圆柱形物体,如钢、PVC和铝制的棒材/管材,以分析尺寸和材料的影响。介绍了本研究的方法和范围,并进行了数值模拟,以优化发射器-接收器配置,并了解超声波信号在穿过含有嵌入式内含物的混凝土时的复杂物理传播现象。通过使用超声波层析系统获得了实验层析图像,该系统的优点是只需要两个超声换能器。软件模拟工具和层析检测系统均由作者开发。所得结果表明,直径大于19mm且嵌入圆柱形试件中的PVC管和钢筋可以被检测到,并且可以使用分段层析图像估计它们的尺寸。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f1/5470475/7d20c1d01119/sensors-17-01085-g001.jpg

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