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Estimation of ground penetrating radar's wave velocity in materials is a critical step to accurately estimate depth of embedded line objects in concrete structures, and wetness of material. Errors of velocity are defined as the deviations between the velocities obtained in various oblique angles and those obtained in the traverse normal to the object orientation in a common offset antenna setting. In this paper, we quantified and corrected the errors of such estimation. GPR traverses were designed to travel in various oblique angles θ (90°, 75°, 60° and 45°) relative to the steel bars at 5 cover depths (55 mm, 85 mm, 115 mm, 145 mm and 175 mm). GPR wave velocity at any position within the lateral detection range of steel bars was measured with simple trigonometry in a semi-automated in-house program. It was found that reduction of oblique angles (i.e. θ<90°) causes flatter hyperbolic reflections and the associated errors of velocity can be as much as 30% in the case of an oblique angle 45° before correction. Such errors were corrected after re-scaling the horizontal travel distance with a multiplication factor of sin θ.
We present the results of a machine learning (ML)- inspired data fusion approach, applied to multi-sensory nondestructive testing (NDT) data. Our dataset consists of Impact-Echo (IE), Ultrasonic Pulse Echo (US) and Ground Penetrating Radar (GPR) measurements collected on large-scale concrete specimens with built–in simulated honeycombing defects. In a previous study we were able to improve the detectability of honeycombs by fusing the information from the three different sensors with the density based clustering algorithm DBSCAN. We demonstrated the advantage of data fusion in reducing the false positives up to 10% compared to the best single sensor, thus, improving the detectability of the defects. The main objective of this contribution is to investigate the generality, i.e. whether the conclusions from one specimen can be adapted to the other. The effectiveness of the proposed approach on a separate full-scale concrete specimen was evaluated.
Laser-induced breakdown spectroscopy (LIBS) is a combination of laser ablation and optical emission spectroscopy. Due to the possibility of direct measurements on the sample surface with a minimum of sample preparation investigations of building materials can be conducted quite fast. In combination with a scanning technique (translation stage or scanning mirrors head) 2D element distributions of harmful species like chlorides and alkalis are evaluated with a sub-mm resolution. By scanning a surface of typically 100 mm x 100 mm the heterogeneity of the material may be considered. LIBS is capable to identify hot spots in element concentration with a resolution of 0.1 mm or even smaller. A LIBS-system for the on-site application on building materials is, in cooperation with system developers and companies which will use this technique for investigation on real structures, under test at BAM. We present an example. Further work will focus on providing guidelines to establish LIBS as a standard procedure for chemical investigations of building materials.
Application of a cross correlation technique for assessment of a non-homogeneous stress field
(2016)
Many researchers have addressed the determination of a homogeneous stress field from the analysis of ultrasound waves, using the theory of acoustoelasticity with Murnaghan´s constants derived for axially loaded specimens with the ultrasound wave path also in the axial direction, or for hydrostatically loaded specimens. However, the use of such strategy for structural healthy monitoring requires the ability to handle nonhomogeneous, arbitrarily oriented stress fields. This paper describes an attempt to evaluate changes in the stress field of a concrete block with an eccentrically placed tendon through acoustoelastic analysis. Pairs of acoustic transducers are placed on the surfaces such that wave paths are parallel to the tendon. A cross correlation technique is used for the accurate assessment of the sound velocity changes, and subsequent application of Murnaghan´s equations for assessing the stress changes. Results are promising with respect to the evaluation for non-homogeneous stress field from ultra sound velocities.