Three-dimensional numerical analysis of plant-soil hydraulic interactions on pore water pressure of vegetated slope under different rainfall patterns

Understanding the pore water pressure distribution in unsaturated soil is crucial in predicting shallow landslides triggered by rainfall,mainly when dealing with different temporal patterns of rainfall intensity.However,the hydrological response of vegetated slopes,especially three-dimensional(3D)slopes covered with shrubs,under different rainfall patterns remains unclear and requires further investigation.To address this issue,this study adopts a novel 3D numerical model for simulating hydraulic interactions between the root system of the shrub and the surrounding soil.Three series of numerical parametric studies are conducted to investigate the influences of slope inclination,rainfall pattern and rainfall duration.Four rainfall patterns(advanced,bimodal,delayed,and uniform)and two rainfall durations(4-h intense and 168-h mild rainfall)are considered to study the hydrological response of the slope.The computed results show that 17%higher transpiration-induced suction is found for a steeper slope,which remains even after a short,intense rainfall with a 100-year return period.The extreme rainfalls with advanced(PA),bimodal(PB)and uniform(PU)rainfall patterns need to be considered for the short rainfall duration(4 h),while the delayed(PD)and uniform(PU)rainfall patterns are highly recommended for long rainfall durations(168 h).The presence of plants can improve slope stability markedly under extreme rainfall with a short duration(4 h).For the long duration(168 h),the benefit of the plant in preserving pore-water pressure(PWP)and slope stability may not be sufficient.

Automatic three-dimensional reconstruction based on four-view stereo vision using checkerboard pattern

An automatic three-dimensional(3D) reconstruction method based on four-view stereo vision using checkerboard pattern is presented. Mismatches easily exist in traditional binocular stereo matching due to the repeatable or similar features of binocular images. In order to reduce the probability of mismatching and improve the measure precision, a four-camera measurement system which can add extra matching constraints and offer multiple measurements is applied in this work. Moreover, a series of different checkerboard patterns are projected onto the object to obtain dense feature points and remove mismatched points. Finally, the 3D model is generated by performing Delaunay triangulation and texture mapping on the point cloud obtained by four-view matching. This method was tested on the 3D reconstruction of a terracotta soldier sculpture and the Buddhas in the Mogao Grottoes. Their point clouds without mismatched points were obtained and less processing time was consumed in most cases relative to binocular matching. These good reconstructed models show the effectiveness of the method.

Reviews on Post-earthquake Reconstruction of Qiang Culture: Three-dimensional Pattern

Through the introduction of disaster situation of Qiang Culture after Wenchuan Earthquake, the paper emphasized that carriers of Qiang Culture had been seriously damaged, the inheritance of Qiang Culture had been affected, and the environment for Qiang Culture was difficult to recover. It highlighted that three-dimensional reconstruction of Qiang Culture should stress the core task and timely and effectively rescue endangered cultural heritages of Qiang Nationality from the perspectives of material and spiritual life. It had explained focuses of three-dimensional pattern construction in detail. In terms of spatial reconstruction, it should reconstruct native culture and history while material culture was constructed, and reconstruct Qiang culture highland by depending on aborigines; in terms of cluster reconstruction, it should give support to large tourism enterprises and perfect tourism chain; in terms of ecological reconstruction, it should enhance construction and demonstration of "ecological protection pilot area of Qiang culture"; in terms of development reconstruction, it should realize coordinated unity between protection and development according to classification protection, characteristic protection and key protection, so as to form the virtuous circle of post-disaster recovery protection and sustainable development.

基于双目视觉的列车轮对表面缺陷及型面参数检测方法

列车轮对表面缺陷及磨耗后的车轮轮型参数对列车安全行驶具有重要影响。搭建一种基于结构光与双目立体视觉相结合的非接触式列车轮对型面检测系统,设计针对车轮滚动圆直径、轮缘高度、轮缘厚度以及车轮擦伤的双目视觉无损检测方法。首先基于迭代最近点(iterative closest point,ICP)算法将各相机采集的车轮型面数据拼接为整体车轮点云三维模型;然后,从该三维模型中提取出滚动圆与轮缘顶点圆,基于最小二乘拟合法分别计算滚动圆直径、轮缘高度、轮缘厚度参数;最后,基于模式匹配方法检测车轮型面是否出现擦伤缺陷,并计算得到擦伤深度。检测结果表明:该列车轮对型面检测系统及表征方法对于滚动圆直径检测误差为0.22 mm,对于轮缘高度与轮缘厚度检测误差分别为–0.08 mm及0.07 mm,最大擦伤深度检测误差为0.18 mm。研究成果可有效检测列车车轮型面参数及擦伤缺陷,具有较强的工程应用价值。

Generative deep-learning-embedded asynchronous structured light for three-dimensional imaging

Three-dimensional(3D)imaging with structured light is crucial in diverse scenarios,ranging from intelligent manufacturing and medicine to entertainment.However,current structured light methods rely on projector-camera synchronization,limiting the use of affordable imaging devices and their consumer applications.In this work,we introduce an asynchronous structured light imaging approach based on generative deep neural networks to relax the synchronization constraint,accomplishing the challenges of fringe pattern aliasing,without relying on any a priori constraint of the projection system.To overcome this need,we propose a generative deep neural network with U-Net-like encoder-decoder architecture to learn the underlying fringe features directly by exploring the intrinsic prior principles in the fringe pattern aliasing.We train within an adversarial learning framework and supervise the network training via a statisticsinformed loss function.We demonstrate that by evaluating the performance on fields of intensity,phase,and 3D reconstruction.It is shown that the trained network can separate aliased fringe patterns for producing comparable results with the synchronous one:the absolute error is no greater than 8μm,and the standard deviation does not exceed 3μm.Evaluation results on multiple objects and pattern types show it could be generalized for any asynchronous structured light scene.

Performance Analysis and Evaluation of Geometric Parameters in Stereo Deflectometry

This paper presents a novel geometric parameters analysis to improve the measurement accuracy of stereo deflectometry.Stereo deflectometry can be used to obtain form information for freeform specular surfaces.A measurement system based on stereo deflectometry typically consists of a fringe-displaying screen,a main camera,and a reference camera.The arrangement of the components of a stereo deflectometry system is important for achieving high-accuracy measurements.In this paper,four geometric parameters of a stereo deflectometry system are analyzed and evaluated:the distance between the main camera and the measured object surface,the angle between the main camera ray and the surface normal,the distance between the fringe-displaying screen and the object,and the angle between the main camera and the reference camera.The influence of the geometric parameters on the measurement accuracy is evaluated.Experiments are performed using simulated and experimental data.The experimental results confirm the impact of these parameters on the measurement accuracy.A measurement system based on the proposed analysis has been set up to measure a stock concave mirror.Through a comparison of the given surface parameters of the concave mirror,a global measurement accuracy of 154.2 nm was achieved.

融合结构信息的深度学习立体匹配算法

针对现有立体匹配算法在边缘区域及视差不连续区域匹配精度的不足,提出了一种融合结构信息的深度学习立体匹配算法。通过简化特征提取网络,并使用Inplace-ABN层替换BatchNorm层和激活函数层,提高卷积提取图像特征的效率;利用结合注意力机制的局部相似性模块提取图像结构特征,与卷积提取到的特征进行融合,丰富图像特征信息;计算输出特征对的相关代价和连接代价,利用相关代价卷积生成注意力权重,滤除连接代价的冗余信息,提升匹配代价计算的精确性;使用简化的沙漏网络,提升网络代价聚合的快速性。算法通过Scene Flow数据集、CREStereo数据集和KITTI数据集进行实验,实验结果表明算法的全部区域端点误差为0.45 px,对第一帧图像全部区域预测错误的比例为1.55%,预测误差大于1 px的像素比例仅有6.87%,证明所提算法相比其他算法在匹配精度上表现优秀,同时验证了算法在问题区域匹配的有效性及优势。

基于双目立体视觉的冻干草莓外部品质等级检测方法研究

[目的]本文旨在建立基于双目立体视觉检测冻干草莓外部品质的方法,实现冻干草莓外部品质等级的无损识别。[方法]应用双目立体视觉技术及像素点匹配算法获取冻干草莓图像中各像素点的视差数据,建立其三维立体模型;以模型体积、图像颜色、形状和纹理品质指标作为特征参数,采用连续投影算法(SPA)筛选出最优特征参数,分别以未筛选的特征参数和筛选后的特征参数建立冻干草莓外部品质等级识别模型,比较各模型的判别分级效果;最后选取最优的识别模型开发冻干草莓外部品质分级软件并进行验证。[结果]使用未经筛选的特征参数对冻干草莓进行品质等级判别时,支持向量机(SVM)模型预测集分级总体准确率为91.7%,偏最小二乘法判别分析(PLS-DA)预测集分级总体准确率为86.7%。使用SPA算法筛选后的特征参数(体积和红色分量均值)所建立的SVM模型和PLS-DA模型分级总体准确率分别为95.0%和81.7%。采用经SPA算法筛选后特征参数构建的SVM模型开发了冻干草莓外部品质识别软件,软件总体准确率可达到90.8%。[结论]基于SPA筛选的特征参数构建的SVM分级预测模型具有较好的判别效果,其建模集和预测集的准确率分别可达97.8%和95.0%。以该模型为基础开发的软件能够实现冻干草莓外部品质的检测。

Perceptible landscape patterns reveal invisible socioeconomic profiles of cities

Urban landscape is directly perceived by residents and is a significant symbol of urbanization development.A comprehensive assessment of urban landscapes is crucial for guiding the development of inclusive,resilient,and sustainable cities and human settlements.Previous studies have primarily analyzed two-dimensional landscape indicators derived from satellite remote sensing,potentially overlooking the valuable insights provided by the three-dimensional configuration of landscapes.This limitation arises from the high cost of acquiring large-area three-dimensional data and the lack of effective assessment indicators.Here,we propose four urban landscapes indicators in three dimensions(UL3D):greenness,grayness,openness,and crowding.We construct the UL3D using 4.03 million street view images from 303 major cities in China,employing a deep learning approach.We combine urban background and two-dimensional urban landscape indicators with UL3D to predict the socioeconomic profiles of cities.The results show that UL3D indicators differs from two-dimensional landscape indicators,with a low average correlation coefficient of 0.31 between them.Urban landscapes had a changing point in2018–2019 due to new urbanization initiatives,with grayness and crowding rates slowing,while openness increased.The incorporation of UL3D indicators significantly enhances the explanatory power of the regression model for predicting socioeconomic profiles.Specifically,GDP per capita,urban population rate,built-up area per capita,and hospital count correspond to improvements of 25.0%,19.8%,35.5%,and 19.2%,respectively.These findings indicate that UL3D indicators have the potential to reflect the socioeconomic profiles of cities.

Three-dimensional face point cloud hole-filling algorithm based on binocular stereo matching and a B-spline

When obtaining three-dimensional(3D)face point cloud data based on structured light,factors related to the environment,occlusion,and illumination intensity lead to holes in the collected data,which affect subsequent recognition.In this study,we propose a hole-filling method based on stereo-matching technology combined with a B-spline.The algorithm uses phase information acquired during raster projection to locate holes in the point cloud,simultaneously extracting boundary point cloud sets.By registering the face point cloud data using the stereo-matching algorithm and the data collected using the raster projection method,some supplementary information points can be obtained at the holes.The shape of the B-spline curve can then be roughly described by a few key points,and the control points are put into the hole area as key points for iterative calculation of surface reconstruction.Simulations using smooth ceramic cups and human face models showed that our model can accurately reproduce details and accurately restore complex shapes on the test surfaces.Simulation results indicated the robustness of the method,which is able to fill holes on complex areas such as the inner side of the nose without a prior model.This approach also effectively supplements the hole information,and the patched point cloud is closer to the original data.This method could be used across a wide range of applications requiring accurate facial recognition.

机器人双目视觉系统的算法研究与实现

针对计算机视觉系统在移动机器人中的应用,对摄像机标定、图像分割、模式识别、目标距离探测以及双目视觉系统在移动机器人导航中的运用进行分析与研究。文章提出了在特定三维场景中,对不同研究对象采取不同处理方式的复合算法,实现了对于机器人视野内简单几何物体的识别,同时使用双目摄像机结构,直接探测出目标物体相对于机器人的深度距离及其方位角度。

经编单层立体提花鞋面织物的花型设计与生产工艺

为优化经编单层立体提花鞋面织物的设计与生产,提出了一种鞋面样板设计及贾卡花型设计的方法,并研究其生产工艺。在鞋面设计方面:通过基线设计法获得鞋面各特征点的位置;归纳了鞋面平行配置、鞋头和鞋后跟交错配置这2种排版方法的设计原则及注意事项;根据鞋面美观性及功能性需求,探究了贾卡花型的设计方法。在生产工艺方面,首先分析了贾卡同向垫纱、反向垫纱的提花原理,然后基于市场上现有单层提花鞋面织物的生产工艺,提出了鞋面原料、组织结构、工艺参数及后整理的快速设计方法,为单层立体提花鞋面织物的设计与生产提供参考依据。

浅层超稠油双水平井SAGD立体井网开发模式研究

针对连续油层厚度大、夹层较发育的SAGD开发油藏,提出一种双层SAGD井网、立体交错部署的开发模式,通过数值模拟研究进行验证,并对生产操作参数进行优化。研究结果表明:采用双层SAGD立体井网可有效提高储量利用率和采油速度,减轻夹层对生产带来的不利影响;双层SAGD蒸汽腔呈现出"孤立发育—上升扩展—相互接触—聚并融合"的发育模式,同时具有汽驱辅助和重力泄油双重开采机理;生产后期,蒸汽腔聚并融合后,上部井组继续注汽,更有利于提高开发效果。双层SAGD立体井网已在风城油田Z区块投入现场应用,取得初步效果。该研究对于类似油藏SAGD高效开发具有借鉴和指导意义。

面向CDIO的工程图学教学改革

CDIO是当前高等教育的新型人才培养模式,以培养国际化工程师为目标。论文介绍了当前图学教育中存在的弊病和CDIO人才培养理念,结合燕山大学等高校实施CDIO教学改革的实践,提出一系列基于CDIO的工程图学教学改革措施。实验证明,该教学模式对于启发与培养大学生动手能力和创造性十分有效,为后续专业课程的学习、毕业设计与科研工作奠定良好基础。

基于虚拟立体靶标的线阵相机标定与分析

针对线阵相机的特点,论文提出了一种线阵相机标定方法。首先,利用设计的平面靶标与相机多次曝光巧妙地构建了虚拟立体标定靶标,通过分析与数学建模得到靶标上标定特征点空间位置与像点的对应关系;其次,分别使用最小二乘法与迭代求解的方法对多个特征点的线性参数超定方程与镜头的非线性畸变参数进行求解,讨论了标定过程中相机与靶标非严格平行时对标定结果的影响;最后,实验室条件下使用论文设计的靶标与方法对线阵相机标定进行实验验证。理论分析与实验结果表明此线阵相机标定方法简单灵活,标定特征点个数不拘泥于靶标的制作,相机与靶标的位置无需严格平行,标定精度高,且具有较好良好的实用工程应用价值。

潜山油藏水平井立体井网井距调整方法

均衡驱替是注水开发井网设计的基本原则。对于以中高角度裂缝发育为主、纵向油层厚度大的潜山油藏,流体重力作用对立体井网均衡驱替有显著的影响。基于渗流理论,以水平井立体五点井网为例,建立了考虑重力作用时生产井见水时间的公式,给出了均衡驱替时注采井距公式,并选取油藏参数计算了均衡驱替时中心水平井的位置;同时,利用数值模拟方法对水平井立体五点井网中心注水井所在的位置进行了优化。结果表明:计算结果与数值模拟优化结果误差为4.73%,在实验允许的范围内,验证了计算公式的可靠性;随着中心注水井逐层上移,纵向上各生产井见水时间差先减小后增大;当注水井S2位于第6层时,生产井S1和S3见水时间差达到最小,实现了均衡驱替,此时采出程度最高,达到42.52%,比S2井位于11层时提高3.84%;均衡驱替时注水井S2到生产井S1和S3的距离之比为2.95。通过调整注水井的位置,减弱了重力作用造成的非均衡驱替,改善了开发效果。

麦-棉-辣-米立体组合种植模式及效益探析

试验研究证明,麦-棉-辣-米立体种植模式采用优化田间结构配置及配套技术措施,农田生态位、作物边际效应及病虫生态控制效应显著,与麦棉、麦辣间套及麦米轮作种植模式相比,其产值分别提高34.1％、27.5％和94.0％,纯收入分别增加8188元/hm^2、6090.5元/hm^2和12066元/hm^2。

都市型郊区循环农业发展模式探讨--以上海市崇明区菜蚓鳝立体种养模式为例

通过阐述上海发展都市型郊区循环农业的必要性,结合崇明国际生态岛建设需求,系统分析了上海崇明区在农业发展模式上的创新升级新模式——"菜蚓鳝"立体种养模式,介绍了该模式的原理与循环路径特点,解析了菜蚓鳝立体模式的经济、生态和社会效益,最后提出了都市型郊区发展立体种养循环农业模式的对策与措施。

咖啡立体栽培及优化模式探讨

立体栽培可以为咖啡生长提供适宜的荫蔽条件。综述目前咖啡生产中的立体栽培模式,并从减少种间竞争等方面对优化模式作进一步的探讨。

重构CDIO特色的工程图学课程体系

论文阐述了工程图学教学现状和不足,结合多年的CDIO工程图学的教学改革经验,概括介绍了如何重构CDIO特色的工程图学课程体系和工程图学教学改革措施。实验证明,该教学模式对于培养大学生动手能力和创造性十分有效,为后续课程的学习、毕业设计与科研工作奠定良好基础。