探地雷达（GPR）在木材无损检测应用中的可行性探讨

简要地介绍了国外已有的树木雷达（TRU）系统，运用其基本原理进行了探地雷达（GPR）应用于木材无损检测的理论可行性分析。由于木材本身的复杂成分，因而其介电性质的影响因素很多，对采集到的电磁波进行客观地解释分析仍存在很大困难。笔者列举了探地雷达的处理、分析和解释的方法，指出若合理、选择性地进行树木雷达分析，可以比较科学准确地对内部腐朽、空洞等特征进行探测。     

探地雷达在箱梁腹板检测中的应用

介绍了探地雷达的工作原理和利用探地雷达技术对箱梁腹板的检测与应用研究,对箱梁腹板典型的质量问题进行总结。结果表明,探地雷达能够对混凝土的质量缺陷给出直观的雷达波形特征,能够判断钢筋保护层厚度,并实现对腹板内波纹管的准确定位。     

探地雷达在公路路基路面检测中的应用

简述了探地雷达检测公路路基路面厚度的基本原理和检测方法。应用美国GSSI公司TerraSIRchSIR-3000探地雷达系统,对连霍高速公路三门峡段路基路面厚度进行了无损检测。计算得出公路路基路面各检测层的平均厚度和标准差,同时通过探地雷达交互式解释方法可以绘制连续清晰的厚度曲线图,有利于探地雷达厚度检测成果的进一步精细解释。     

探地雷达在工程检测中的应用与发展

着重介绍了探地雷达的工作原理及其测试方法。指出当前应用中存在的若干问题,提出改进的办法和措施,以及促使智能化发展的几点设想,以期探地雷达能在工程勘查,水利隐患探测和结构无损检测中得以广泛推广与应用,力求能为更好地把握和控制工程质量提供技术支撑和参考。     

激光、微波和红外热成像检测技术在中国——庆祝中国机械工程学会无损检测分会成立三十周年

介绍学会成立30年来激光、微波和红外等无损检测新方法的发展进程。着重介绍了激光全息干涉、电子散斑干涉、微波探地雷达、红外热成像和热波成像等新技术近年来在国内的研究应用情况。对新技术的应用前景进行了展望。     

探地雷达在混凝土板钢筋检测中的应用

介绍探地雷达技术应用于混凝土结构无损检测的原理,针对其在确定钢筋直径以及钢筋笼中单根钢筋位置的检测难点,制作了一块带有多根单独钢筋及双层钢筋网的混凝土板,并使用1.2GHz的雷达天线采用反射法对板进行了检测。检测结果表明,雷达可以分辨出双层钢筋的位置,并给出估计钢筋直径的方法以及可分辨钢筋的最小间距。     

水闸底板渗流隐患的探地雷达检测

介绍了探地雷达的工作原理,应用探地雷达技术检测佛山市沙口水利枢纽引水闸底板的渗流隐患,分析研究了渗流隐患区域的探地雷达图像特征和隐患的定性识别方法。检测结果表明,该技术可有效地检测水闸底板的渗流隐患。     

磁粉探伤发展现状与展望

介绍我国磁粉探伤设备，探伤材料发展现状，介绍磁橡胶（ＭＲＩ）法和橡胶铸型（ＭＴ－ＲＣ）法及透明胶带测裂纹高度法和磁粉探粉标准化的状况等。     

核电站安全壳的微波探地雷达腐蚀检测

介绍了核电站安全壳钢板混凝土中钢衬的腐蚀检测技术,使用探地雷达技术对钢衬腐蚀进行检测,并对其反射图谱进行分析。结果表明:采用探地雷达微波技术对核电站安全壳进行在役检查是保证内衬钢板质量的根本措施。     

探地雷达数据处理软件接口编制及应用

为实现不同类型探地雷达的数据处理、建模、模拟和显示,以RIS-K2型探地雷达为例,研究其数据结构和数据排列方式,探讨探地雷达接口编制、编程实现数据的读取、显示及处理,并将所编程序嵌入MATGPR程序中,实现了对RIS-K2,GSSI,Pulse EKKO,SU,SEG-Y和RA-MAC等六种探地雷达进行数据处理的功能,为不同类型探地雷达用户提供了数据处理的自由开放平台.     

In situ measurements of hot-mix asphalt dielectric properties

Twelve different flexible pavement sections, which comprised different layers/materials, are incorporated in the Virginia Smart Road test facility. These sections provide a good opportunity to explore the feasibility of using ground penetrating radar (GPR) to assess pavements and to verify its practicality. Thirty-one copper plates, serving as a reflecting material, were placed during construction at different layer interfaces throughout the pavement sections. Results show that enough radar energy is reaching the subgrade, but due to low dielectric contrast between some pavement materials, energy is not reflected back. In these cases, the copper plates indicate where the interface between each two layers occurs. Reflections from the copper plates are also used to determine the dielectric constant of pavement materials over the GPR frequency range. This paper presents an overview of the Virginia Smart Road test facility, data obtained from different sections using two GPR systems, and a method to calculate the complex dielectric constant of hot-mix asphalt over the frequency range of 750–1750 MHz using an air-coupled GPR system.     

Understanding depth-amplitude effects in assessment of GPR data from concrete bridge decks

The variation of concrete cover thickness on bridge decks has been observed to significantly affect the rebar reflection amplitude of the ground penetrating radar signal. Several depth correction approaches have been previously proposed in which it is assumed that, for any bridge, at least a portion of the deck area is sound concrete. The 90th percentile linear regression is a commonly used procedure to extract the depth-amplitude relationship of the assumed sound concrete. It is recommended herein that normalizing the depth-dependent amplitudes be divided into two components. The first component takes into account the geometric loss due to inverse-square effect and the dielectric loss caused by the dissipation of electromagnetic energy in sound concrete. The second component is the conductive loss as a result of increased free charges associated with concrete deterioration. Whereas the conventional depth correction techniques do not clearly differentiate the two components and tend to incorporate both in the regression line, they are separately addressed in this research. Specifically, while the first component was accounted for based on a library of GPR signals collected from sound areas of twenty four bare concrete bridge decks, the conductive loss caused by an increased conductivity is linearly normalized by the two-way travel time. The implementation of the proposed method in two case studies showed that, while the method significantly improves the accuracy of GPR data analysis, the conventional methods may lead to a loss of information regarding the background attenuation that would indicate the overall deterioration of bridge decks.     

Effects of antenna-target polarization and target-medium dielectric contrast on GPR signal from non-metal pipes using FDTD simulation

Ground penetrating radar (GPR) is widely used especially in subsurface pipes investigation and detection. The general practice is that the parallel antenna-target polarization is used for metal pipe GPR imaging and normal antenna-target polarization for non-metal pipe imaging. However, such practice does not always produce optimized results. The main reason is that the dielectric contrast in a non-metal pipes GPR imaging play an important roles in generating a good GPR signal. The research intends to highlight these issues by incorporating a finite-difference time domain (FDTD) simulation for several cases. The important observation is that antenna-target polarization as well as the dielectric contrast are two important criteria in determining a good GPR signal for non-metal pipes imaging.     

Validation of mobile LiDAR surveying for measuring pavement layer thicknesses and volumes

Mobile LiDAR surveying is currently one of the most popular topics in road inspections. This non-destructive technology is suitable for collecting infrastructure inspection data related to 3D geometry and radiometry. Ground penetrating radar (GPR) is traditionally used to measure pavement thickness, though this technique requires reference data (cores) when surveying in a ground-coupled configuration.Within this work, a new alternative method to GPR has been studied for determining pavement layer thicknesses and volumes. We analyze the performance of mobile LiDAR technology in this scope and test its accuracy compared to the results obtained with a ground-coupled 2.3-GHz GPR antenna. The findings presented here are based on field data collected from the Ourense–Celanova highway, in Northwestern Galicia. The results showed the potential of the Lynx Mobile Mapper to obtain the designed pavement thickness of newly constructed roadways with errors that are always less than 1.5 cm.     

GPR signal de-noising by discrete wavelet transform

Ground penetrating radar (GPR) is a non-destructive investigation tool used for several applications related to civil infrastructures; including buried objects detection and structural condition evaluation. Although GPR can be effectively used to survey structures, signal analysis can be sometimes challenging. The GPR signals can be easily corrupted by noise because the GPR receiver has usually an ultra-wide bandwidth (UWB). The noise collected by the system can easily mask relatively weak reflections resulting from the inhomogeneities within the surveyed structure; especially when they are at a relatively deep location. This paper presents the use of discrete wavelet transform (DWT) to de-noise the GPR signals. Various mother wavelets were used in this study to de-noise experimental GPR signals collected from flexible pavements. The performance of wavelet de-noising was evaluated by computing the signal-to-noise ratio (SNR) and the normalized root-mean-square error (NRMSE) after de-noising. The study found that wavelet de-noising approach outperforms traditional frequency filters such as the elliptic filter. At the same level of decomposition, the Daubechies order 6 and Symlet order 6 outperform the Haar and Biorthogonal mother wavelets when de-noising GPR signals by soft thresholding.     

GPR performances for thickness calibration on road test sites

This paper presents ground penetrating radar (GPR) experiments conducted on a number of road test sites. In its capacity as a State civil engineering research organization, the Laboratoire Central des Ponts et Chaussées (LCPC) possesses large-scale testing facilities, such as a circular pavement fatigue test track, ideal for road-related research. This particular facility is composed of several sections of different known structures especially well-adapted for GPR investigations. Our study of GPR techniques made use of a commercial system for measuring asphalt layer thickness.Various road structures have been examined with a GSSI system. Cores have been drilled and permittivity measurements performed in the laboratory. The initial study reveals a comparison between thickness measured by coring and that calculated from both measured permittivities and GPR-selected times.A second study has consisted of avoiding calibration with core drilling, by means of recording GPR signals with a non-destructive testing technique on the multi-layer structures (i.e. common middle point). A numerical reconstruction has then been developed in order to calculate the thickness and velocity of each layer from experimental data. When compared with the cored samples, results show a sufficient level of accuracy in the first two or three layer thickness measurements to satisfy the needs of road facility managers.     

Automatic detection of multiple pavement layers from GPR data

One of the problems encountered in the nondestructive testing of pavements with ground penetrating radar (GPR) is the detection of multiple-layer reflections within the GPR return. Detecting reflections is especially problematic when the pavement layers are thin with respect to the probing pulse width, in which case overlapping between the reflected pulses occurs, causing the weak reflections to be masked by the stronger reflections in their vicinity. In this study, the problem is solved by iteratively detecting the strong reflections present within the GPR signal using either a threshold or a matched filter detector. The detected pulses are then used in a reflection model to synthesize a signal “similar” to the measured GPR signal in the least-squares sense. The synthesized signal is then subtracted from the measured signal to reveal the masked weak reflections, which are later detected iteratively using the same method. This technique was successfully applied to field GPR data collected from an experimental pavement site: the Virginia Smart Road.