Condition Monitoring of Ground Anchorages by Dynamic Impulses: GRANIT System

The GRANIT system operates by applying an impulse of known force by means of an impact device that is attached to the tendon of the anchorage. The vibration response signals resulting from this impulse are complex in nature and require analysis to be undertaken in order to extract information from the vibrational response signatures that is relevant to the condition of the anchorage. In the system, the complicated relationship that exists between characteristics of an anchorage and its response to an impulse is identified and learned by a novel artificial intelligence network based on artificial intelligence techniques.The results presented in this paper demonstrate the potential of the GRANIT system to diagnose the integrity of ground anchorages at a site near Stone, England, by using a trained neural network capable of diagnosing the post-tension level of the anchorage. This neural network was used for the diagnosis of load in a second ground anchorage adjacent to the original anchorage used for the training of the neural network. Further tests were taken with a different anchor head configuration of the anchorage and a different relationship between the signature response of the anchorage to an applied impulse and its post-tension level was found.Problems encountered during the diagnosis of this second set of test signatures by the trained neural network are investigated with the use of a lumped parameter dynamic model. This model is able to identify the parameters in the anchorage system that affect this change in response signature. The results from the investigation lead to a new form of classification for the installed anchorages, based on their anchor head configuration.Laboratory strand anchorage tests were undertaken in order to compare with and validate the results obtained from the field tests and the lumped parameter dynamic model.     

Processing and characterization of epoxy/clay nanocomposites

Nanocomposite materials consisting of an epoxy matrix and silicate clay particles have been processed and characterized mechanically. The clay material used was a modified natural montmorillonite. The clay particles consisted of 1 nm thick layers with aspect ratios in the range of 100–1000. The clay particles were mixed with acetone and sonicated, then mixed with the polymer, deaerated and cured. The ultimate objective of processing was to produce a polymer/clay nanocomposite with separated (exfoliated) platelets, dispersed as uniformly as possible. Samples were prepared with clay concentrations of up to 10 wt%. The process used resulted in limited exfoliation but mostly intercalation, i.e., infusion of polymer between the silicate layers and increase of interlayer spacing. The characteristics of the nanocomposite were assessed by transmission electron microscopy and x-ray diffraction. Results from these observations show that the basal spacing of clay platelets increased from an initial pre-processing value of 1.85 nm to 4.5 nm. Enhancement of mechanical properties was measured by tensile testing of coupons. Stiffness increases of up to 50% over that of the unfilled epoxy were measured for clay concentrations of 5 wt%. Strength increases were also measured for low clay concentrations and low strain rate loading. Micromechanics modeling of mechanical behavior is discussed as a function of clay platelet dispersion.     

Strain analysis for moiré interferometry using the two-dimensional continuous wavelet transform

In this paper, we introduce the two-dimensional continuous wavelet transform for the automated strain analysis of the moiré interference fringe pattern. The Fourier transform method has been widely used for automated analysis of an optical interference fringe pattern. However, this method is hardly applicable to the analysis of the fringe pattern, which includes large displacement range or discontinuities. We show the advantages of the wavelet transform method by applying it to experimental results on composite laminates.     

进气道实验中动态数据采集及处理方法研究

本文介绍了进气道实验中动态数据采集及处理方法，研究了滤波器截止频率以及进气道不同流量对动态畸变指数的影响，对在干扰状态下得到的数据以传统方法、统计方法、误差方法进行了分析及处理，并对所得到的实时数据进行了频谱分析。     

Toward automatic evaluation of defect detectability in infrared images of composites and honeycomb structures

Non-destructive testing (NDT) refers to inspection methods employed to assess a material specimen without impairing its future usefulness. An important type of these methods is infrared (IR) for NDT (IRNDT), which employs the heat emitted by bodies/objects to rapidly and noninvasively inspect wide surfaces and to find specific defects such as delaminations, cracks, voids, and discontinuities in materials. Current advancements in sensor technology for IRNDT generate great amounts of image sequences. These data require further processing to determine the integrity of objects. Processing techniques for IRNDT data implicitly looks for defect visibility enhancement. Commonly, IRNDT community employs signal to noise ratio (SNR) to measure defect visibility. Nonetheless, current applications of SNR are local, thereby overseeing spatial information, and depend on a-priori knowledge of defect’s location. In this paper, we present a general framework to assess defect detectability based on SNR maps derived from processed IR images. The joint use of image segmentation procedures along with algorithms for filling regions of interest (ROI) estimates a reference background to compute SNR maps. Our main contributions are: (i) a method to compute SNR maps that takes into account spatial variation and are independent of a-priori knowledge of defect location in the sample, (ii) spatial background analysis in processed images, and (iii) semi-automatic calculation of segmentation algorithm parameters. We test our approach in carbon fiber and honeycomb samples with complex geometries and defects with different sizes and depths.     

Development of microscale pattern for digital image correlation up to 1400 °C

Speckle patterns to be used for digital image correlation (DIC) at the micrometer level up to 1400 °C were fabricated by several methods. The quality of the patterns before and after heating was evaluated in terms of the mean intensity gradient (MIG) and the speckle size distribution. The displacement accuracy in simulative translation of images showed that the MIG alone was not enough to evaluate the pattern properties; a large MIG, an even speckle size distribution, and a wide speckle size range pattern were required for a good DIC. The reaction between the patterning material and substrate, the cracking of speckles, and the plastic flow of patterning material may cause changes in the pattern morphology at high temperature. Two patterning methods, spraying a mixture of ceramics powder and binder by a fine-nozzle air brush and abrading a polished surface, yielded a small pattern with high MIG values and even size distributions that was stable at 1400 °C. The potential of the fabricated patterns was shown by measuring the coefficient of thermal expansion of polycrystalline Al₂O₃ from 800 °C to 1400 °C.     

Surface strain-field determination of tympanic membrane using 3D-digital holographic interferometry

In order to increase the understanding of soft tissues mechanical properties, 3D Digital Holographic Interferometry (3D-DHI) was used to quantify the strain-field on a cat tympanic membrane (TM) surface. The experiments were carried out applying a constant sound-stimuli pressure of 90 dB SPL (0.632 Pa) on the TM at 1.2 kHz. The technique allows the accurate acquisition of the micro-displacement data along the x, y and z directions, which is a must for a full characterization of the tissue mechanical behavior under load, and for the calculation of the strain-field in situ. The displacements repeatability in z direction shows a standard deviation of 0.062 µm at 95% confidence level. In order to realize the full 3D characterization correctly the contour of the TM surface was measured employing the optically non-contact two-illumination positions contouring method. The x, y and z displacements combined with the TM contour data allow the evaluation its strain-field by spatially differentiating the u(m,n), v(m,n), and w(m,n) deformation components. The accurate and correct determination of the TM strain-field leads to describing its elasticity, which is an important parameter needed to improve ear biomechanics studies, audition processes and TM mobility in both experimental measurements and theoretical analysis of ear functionality and its modeling.     

使用压缩感知的遥感图像振荡畸变几何校正方法

卫星平台振动和反射镜震颤会引起遥感图像中的振荡畸变。这类畸变难以通过常用的几何校正方法消除。对此,提出了一种使用压缩感知的几何校正方法。该方法基于有理函数模型(RFM)进行几何校正。在校正过程中,利用初始的RFM计算出地面控制点(GCPs)在图像中的投影坐标与实际成像坐标之间的偏差(称为投影偏差),以地面控制点处的投影偏差作为采样值,使用压缩感知技术重构出所有像元处的投影偏差,并据此对RFM进行像方补偿;利用经过补偿的RFM进行遥感图像纠正。通过补偿,消除了振荡畸变引起的RFM模型误差,进而提高校正性能。利用实测数据验证了该方法的有效性,并通过仿真数据分析了地标点的数量与分布对该几何校正方法性能的影响。     

Gaussian pre-filtering for uncertainty minimization in digital image correlation using numerically-designed speckle patterns

This paper discusses the effect of pre-processing image blurring on the uncertainty of two-dimensional digital image correlation (DIC) measurements for the specific case of numerically-designed speckle patterns having particles with well-defined and consistent shape, size and spacing. Such patterns are more suitable for large measurement surfaces on large-scale specimens than traditional spray-painted random patterns without well-defined particles. The methodology consists of numerical simulations where Gaussian digital filters with varying standard deviation are applied to a reference speckle pattern. To simplify the pattern application process for large areas and increase contrast to reduce measurement uncertainty, the speckle shape, mean size and on-center spacing were selected to be representative of numerically-designed patterns that can be applied on large surfaces through different techniques (e.g., spray-painting through stencils). Such “designer patterns” are characterized by well-defined regions of non-zero frequency content and non-zero peaks, and are fundamentally different from typical spray-painted patterns whose frequency content exhibits near-zero peaks. The effect of blurring filters is examined for constant, linear, quadratic and cubic displacement fields. Maximum strains between ±250 and ±20,000 µε are simulated, thus covering a relevant range for structural materials subjected to service and ultimate stresses. The robustness of the simulation procedure is verified experimentally using a physical speckle pattern subjected to constant displacements. The stability of the relation between standard deviation of the Gaussian filter and measurement uncertainty is assessed for linear displacement fields at varying image noise levels, subset size, and frequency content of the speckle pattern. It is shown that bias error as well as measurement uncertainty are minimized through Gaussian pre-filtering. This finding does not apply to typical spray-painted patterns without well-defined particles, for which image blurring is only beneficial in reducing bias errors.     

Optical extensometer and elimination of the effect of out-of-plane motions

A novel optical extensometer is developed to estimate the local uniform strain on planar surface accurately. The proposed system consists of a shared large format lens and two image sensors, which acquire pairs of images of two isolated small regions on the object surface simultaneously. Digital image correlation (DIC) algorithm is applied to determine the relative displacement between gauge points designated on recorded pairs of images. Then local strain can be extracted after dividing the relative displacement by the scale distance. Moreover, a special experimental setup called “correction sheet” is used to eliminate the virtual strain induced by out-of-plane motions. Uni-axial tensile experiments are performed to validate the reliability and resolution of the optical extensometer, and the measurement results demonstrate that the resolution of the optical extensometer achieves 2–3 με.