Investigation on time scales in a low Reynolds number jet flow using particle-tracking velocimetry

The near flow field of an axisymmetric water jet at Reynolds numbers between 2000 and 5000 is investigated using Particle-Tracking Velocimetry. Measurements are taken in the longitudinal section (along the mean flow) and in cross-sections (orthogonal to the mean flow). From the former, correlation coefficients of the two in-plane velocity components in a Lagrangian framework are obtained: thus Lagrangian integral scales can be computed. Those of the streamwise velocity (axial) component increase on moving away from the centreline, whereas the opposite happens for the vertical velocity (radial) component: integral time scales of the two components are almost equal at the interface between jet and ambient fluids. On the other hand, integral scales are almost constant or increase slightly with the axial direction. In cross-sections, fluid ejection and injection from the jet centreline are observed to be connected to counter-rotating vortices (mushroom): their number and size change with Reynolds number in agreement with results from other authors. The maximum ejection velocity (orthogonal to the mean jet flow), at 3 nozzle diameters downstream of the outlet, is found to be one half of the mean outlet velocity.     

Shape memory behavior in Fe3Al-modeling and experiments

The Fe₃Al alloy with D0₃ structure exhibits large recoverable strains due to reversible slips. Tension and compression experiments were conducted on single crystals of Fe₃Al, and the onset of slip in forward and reverse directions were obtained utilizing high-resolution digital image correlation technique. The back stress provides the driving force for reversal of deformation upon unloading, resulting in a superelastic phenomenon as in shape memory alloys. Using density functional theory simulations, we obtain the energy barriers (GSFE – generalized stacking fault energy) for {1?1?0}〈1?1?1〉 and {1?1?2}〈1?1?1〉 slips in D0₃ Fe₃Al and the elastic moduli tensor, and undertake anisotropic continuum calculations to obtain the back stress and the frictional stress responsible for reversible slip. We compare the theoretically obtained slip stress magnitudes (friction and back stress) with the experimental measurements disclosing excellent agreement.     

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.     

Optical coherence tomography based particle image velocimetry (OCT-PIV) of polymer flows

The measurement of spatially resolved velocity distributions is crucial for modelling flow and for understanding properties of materials produced in extrusion processes. Traditional methods for flow visualization such as particle image velocimetry (PIV) rely on optically transparent media and cannot be applied to turbid polymer melts. Here we present optical coherence tomography as an imaging technique for PIV data processing that allows for measuring a sequence of time resolved images even in turbid media. Time-resolved OCT images of a glass-fibre polymer compound were acquired during an extrusion process in a slit die. The images are post-processed by ensemble cross-correlation to calculate spatially resolved velocity vector fields. The results compared well with velocity data obtained by Doppler-OCT. Overall, this new technique (OCT-PIV) represents an important extension of PIV to turbid materials by the use of OCT.     

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.     

基于小波高频距离像的红外小目标检测

针对远距离复杂背景下红外小目标检测问题,本文提出了一种基于小波高频距离像的方法。该方法首先将处理空间变换到小波域,通过分析残留背景、目标和噪声系数在高频子带的差异,定义基于邻域均值的子带系数表达形式,构造高频子带系数的中心向量,对小波高频图像进行综合形成距离像,得到红外复杂背景的抑制结果。在此基础上,利用恒虚警率算法将单帧背景抑制图像分割成候选目标、残留背景和噪声像素点。最后,在时间域基于目标运动的相关性,利用管道滤波实现红外小目标的最终检测。仿真实验结果表明,相对于经典算法,本文方法可以实现对红外复杂背景的有效抑制,增强目标信号的强度,准确稳定的从红外复杂背景中检测出小目标。     

基于机器视觉的车辆保险盒在线检测研究

摘要: 车辆保险盒作为汽车电控系统中的一个重要的元器件,其质量好坏直接影响汽车的性能,传统的车辆保险盒检测主要依靠人工检测,检测费时费力,针对该问题,提出一种基于视觉的车辆保险盒在线检测方法,分析了产品图像校正到标准模板图像的位置误差,采用SURF(Speeded Up Robust Feature)算法和平面单应性理论将待检产品图像变换到标准模板位置,利用颜色直方图匹配和模板匹配完成保险盒上元件的检测。实验结果证明,该方法检测效率高,稳定可靠,能够满足在线检测的要求,具有一定实用价值。