Under the strategic framework of rural revitalization and agricultural modernization, Xinjiashan Specialty Coffee Base, located in Zaotang Village, Lujiang Town, Longyang District, Baoshan City, has been proactively i...Under the strategic framework of rural revitalization and agricultural modernization, Xinjiashan Specialty Coffee Base, located in Zaotang Village, Lujiang Town, Longyang District, Baoshan City, has been proactively investigating innovative models for agricultural development. Through extensive communication and collaboration, this base has established close partnerships with research institutions including Kunming University of Science and Technology, Baoshan University, and Yunnan Academy of Agricultural Sciences, with a commitment to thoroughly exploring the potential for resource recycling and ecological complementarity. An innovative four-in-one three-dimensional integrated planting system incorporating "coffee, bananas, green manure, and bees" has been implemented. Concurrently, technological and digital management strategies have been comprehensively integrated to improve planting efficiency. Under this model, the proportion of specialty coffee attains 71%, and the per-unit yield is 17% greater than that of the conventional planting model. This approach not only substantially enhances economic returns but also promotes the integrated development of ecological and social benefits, offering a valuable practical example and experiential reference for the specialty and sustainable advancement of the coffee industry in comparable regions.展开更多
Aerial surveys are dynamic and continuous processes,and there are different height distributions of the ground in the measurement area,which leads to problems such as overlapping measurement areas and inaccurate altit...Aerial surveys are dynamic and continuous processes,and there are different height distributions of the ground in the measurement area,which leads to problems such as overlapping measurement areas and inaccurate altitude correction during the survey process.Commonly used terrain correction methods are based on the concept of finite elementization of ground surface radioactive sources,using GPS coordinates,radar altitude,and ground elevation distribution information from aerial surveys,combined with the sourceless efficiency calibration method to construct a response matrix,which is then inverted for surface nuclide content.However,most of the sourceless efficiency calibration methods used are numerical calculations that consider the body detector as a point detector and do not consider the changes in intrinsic detection efficiency under different incident directions of gamma rays.Therefore,when the altitude of the measurement area varies significantly or the flight altitude of the aerial survey is relatively low,such sourceless efficiency calibration method calculations tend to have a large bias,which affects the accuracy of the terrain correction.To address the above problems,this study employs a novel sourceless efficiency calibration method based on the Boolean operation of the ray deposition process and simplifies the traditional body source measurement model to a surface source measurement model to achieve fast and accurate efficiency calibration.Then,through the discretization of the measurement process,the static measurement process is superposed as equivalent to the dynamic measurement process,and the dynamic measurement response matrix is built and optimized based on the calibration method.Finally,the PSO-MLEM algorithm was used to solve the dynamic measurement response matrix to achieve dynamic terrain correction of aerial survey data.Analysis of the Baiyun'ebo test area revealed that,after applying dynamic terrain correction,the inverted anomalies in uranium(eU),thorium(eTh),and potassium(K)concentrations were closer to ground measurements(within 5.72%-30.79%)and exhibited clearer anomaly boundaries compared to traditional height-based corrections.However,owing to the inherent statistical fluctuations and characteristics of matrix inversion,higher measurement values tend to absorb lower ones,potentially enlarging the anomalous regions.Nevertheless,the highanomaly regions after inversion largely coincided with the ground truth validation,demonstrating that the proposed method can effectively correct airborne gamma spectrometry data.展开更多
According to the Mindlin plate theory and the first-order piston theory,this work obtains accurate closed-form eigensolutions for the flutter problem of three-dimensional(3D)rectangular laminated panels.The governing ...According to the Mindlin plate theory and the first-order piston theory,this work obtains accurate closed-form eigensolutions for the flutter problem of three-dimensional(3D)rectangular laminated panels.The governing differential equations are derived by the Hamilton's variational principle,and then solved by the iterative Separation-of-Variable(i SOV)method,which are applicable to arbitrary combinations of homogeneous Boundary Conditions(BCs).However,only the simply-support,clamped and cantilever panels are considered in this work for the sake of clarity.With the closed-form eigensolutions,the flutter frequency,flutter mode and flutter boundary are presented,and the effect of shear deformation and aerodynamic damping on flutter frequencies is investigated.Besides,the relation between panel energy and the work of aerodynamic load is discussed.The numerical comparisons reveal the following.(A)The flutter eigenvalues obtained by the present method are accurate,validated by the Finite Element Method(FEM)and the Galerkin method.(B)When the span-chord ratio is larger than 3,simplifying a 3D panel to 2D(two-dimensional)panel is reasonable and the relative differences of the flutter points predicted by the two models are less than one percent.(C)The reciprocal relationship between the mechanical energy of the panel and the work done by aerodynamic load is verified by using the present flutter eigenvalues and modes,further indicating the high accuracy of the present solutions.(D)The coupling of shear deformation and aerodynamic damping prevents frequency coalescing.展开更多
This paper proposes a state-of-the-art three-dimensional Voronoi cell finite element method(3D VCFEM)aimed at investigating the mechanical properties of particle-reinforced composites(PRCs)in space under different mic...This paper proposes a state-of-the-art three-dimensional Voronoi cell finite element method(3D VCFEM)aimed at investigating the mechanical properties of particle-reinforced composites(PRCs)in space under different microstructural properties.Firstly,the modified residual energy generalized function of 3D VCFEM was proposed by applying the hybrid stress element method,and the element format of the 3D Voronoi element was constructed.On this basis,the interaction between the matrix and the inclusions was considered,and the higher-order stress function including the interaction stress term was constructed.Secondly,to solve the difficulty of integrating easily due to the complexity and irregularity of the integration region in space,Delaunay tetrahedra were introduced within the 3D Voronoi element for mesh refinement.It simplified the integration process.Finally,to verify the accuracy and efficiency of the 3D VCFEM model,comparative models of 3D VCFENM and FEM were established for analysis and discussion.The stress field and strain field were compared and analyzed for the first time.An example was also given for the presence of a large number of randomly distributed inclusion particles.The results showed that under the same accuracy,3D VCFEM had the advantages of convenient mesh delineation and high computational efficiency compared with FEM,which provided a new way of thinking to analyze the actual PCRs.展开更多
针对弱纹理和变光照环境下基于点特征的视觉SLAM(simultaneous localization and mapping)算法轨迹漂移的问题,提出了一种基于改进自适应阈值ELSED算法(Adaptive-ELSED)的快速点线融合双目视觉SLAM算法。通过在ELSED算法中添加自适应阈...针对弱纹理和变光照环境下基于点特征的视觉SLAM(simultaneous localization and mapping)算法轨迹漂移的问题,提出了一种基于改进自适应阈值ELSED算法(Adaptive-ELSED)的快速点线融合双目视觉SLAM算法。通过在ELSED算法中添加自适应阈值矩阵,动态调整不同光照条件下梯度阈值,并使用长度抑制和短线合并策略,提高线特征的质量。利用基于双目几何约束和图像结构相似性(SSIM)进行快速线段特征三角化。基于历史位姿及误差分析获取初始位姿,通过自适应因子实现光束法平差过程中点线特征的更有效融合。实验结果表明,所提算法在提高线特征质量的同时,耗时仅为LSD算法的50%,线特征匹配速度较传统LBD算法提升67%,挑战性场景下轨迹误差较ORB-SLAM3降低62.2%,系统的平均跟踪帧率为27帧/s,在保证系统实时性的同时,显著提升了系统在弱纹理、变光照环境下的精度和鲁棒性。展开更多
目前多数视觉即时定位与地图构建(simultaneous localization and mapping,SLAM)方案都是通过提取环境中的特征点来估计位姿,在纹理较少的弱纹理环境中仍存在较大的局限性。为此,在SLAM系统中引入线特征以保证系统能在弱纹理场景中稳定...目前多数视觉即时定位与地图构建(simultaneous localization and mapping,SLAM)方案都是通过提取环境中的特征点来估计位姿,在纹理较少的弱纹理环境中仍存在较大的局限性。为此,在SLAM系统中引入线特征以保证系统能在弱纹理场景中稳定运行。但目前融合点线的视觉SLAM方案存在实时性和精度不足的问题,因此提出基于改进点线特征融合的的视觉惯性SLAM算法。算法前端中,采用FAST(features from accelerated segment test)角点作为特征点提取算法,对ELSED(enhanced line segment detection)算法进行增加短线合并、梯度阈值参数调整,并将四叉树均匀化分布特征点扩展到点线特征,提出改进的点线特征提取算法,减少高纹理区域和特征分布不均的情况对系统精度的影响。对点线特征的跟踪,均采用改进型光流法追踪,将惯性测量单元(inertial measured unit,IMU)得到的位姿信息和已知的特征点深度计算光流法的初值,代替原本的图像金字塔迭代过程,从而节省计算资源,满足系统的实时性。最后,在实际场景中将该系统与优秀的开源方案进行实验对比,验证了所提算法的实时性和精确性。实验表明,本算法可为工业巡检、仓储物流等场景下的机器人提供高鲁棒性定位解决方案,具有显著的产业应用前景。展开更多
针对动态场景下视觉SLAM(Simultaneous Localization and Mapping)系统中深度学习分割网络实时性不足,以及相机非期望运动导致位姿估计偏差的问题,提出一种基于跨域掩膜分割的视觉SLAM算法.该算法采用轻量化YOLO-fastest网络结合背景减...针对动态场景下视觉SLAM(Simultaneous Localization and Mapping)系统中深度学习分割网络实时性不足,以及相机非期望运动导致位姿估计偏差的问题,提出一种基于跨域掩膜分割的视觉SLAM算法.该算法采用轻量化YOLO-fastest网络结合背景减除法实现运动物体检测,利用深度图结合深度阈值分割构建跨域掩膜分割机制,并设计相机运动几何校正策略补偿检测框坐标误差,在实现运动物体分割的同时提升处理速度.为优化特征点利用率,采用金字塔光流对动态特征点进行帧间连续跟踪与更新,同时确保仅由静态特征点参与位姿估计过程.在TUM数据集上进行系统性评估,实验结果表明,相比于ORB-SLAM3算法,该算法的绝对位姿误差平均降幅达97.1%,与使用深度学习分割网络的DynaSLAM和DS-SLAM的动态SLAM算法相比,其单帧跟踪时间大幅减少,在精度与效率之间实现了更好的平衡.展开更多
针对复杂室内环境中视觉同步定位与建图(simultaneous localization and mapping,SLAM)算法在高质量三维重建中的效率问题,提出了一种高效的神经辐射场SLAM(NeRF-SLAM)算法——EN-SLAM。该算法利用多分辨率哈希网格表示场景,结合其快速...针对复杂室内环境中视觉同步定位与建图(simultaneous localization and mapping,SLAM)算法在高质量三维重建中的效率问题,提出了一种高效的神经辐射场SLAM(NeRF-SLAM)算法——EN-SLAM。该算法利用多分辨率哈希网格表示场景,结合其快速收敛特性及高频局部特征表示能力,显著提升了三维重建效率。为进一步增强未观测区域的表面连贯性及细节补全,算法引入球谐函数进行方向编码,从而保证了重建结果的一致性与细节完整性,同时提高实时性。此外,设计了一种信息引导采样策略,优先采样对重建贡献较大的光线,同时实现全局优化(BA)在所有关键帧上的高效执行。在Replica、ScanNet、TUM RGBD和Neural RGB-D数据集上的实验表明,该算法在提高建图精度、跟踪精度及渲染质量的同时,在Replica数据集上的运行时间较iMAP、NICE-SLAM、Vox-Fusion、ESLAM和Co-SLAM分别提升了98.99%、92.80%、91.97%、63.77%和19.15%,且场景重建完成率达到94.14%。展开更多
文摘Under the strategic framework of rural revitalization and agricultural modernization, Xinjiashan Specialty Coffee Base, located in Zaotang Village, Lujiang Town, Longyang District, Baoshan City, has been proactively investigating innovative models for agricultural development. Through extensive communication and collaboration, this base has established close partnerships with research institutions including Kunming University of Science and Technology, Baoshan University, and Yunnan Academy of Agricultural Sciences, with a commitment to thoroughly exploring the potential for resource recycling and ecological complementarity. An innovative four-in-one three-dimensional integrated planting system incorporating "coffee, bananas, green manure, and bees" has been implemented. Concurrently, technological and digital management strategies have been comprehensively integrated to improve planting efficiency. Under this model, the proportion of specialty coffee attains 71%, and the per-unit yield is 17% greater than that of the conventional planting model. This approach not only substantially enhances economic returns but also promotes the integrated development of ecological and social benefits, offering a valuable practical example and experiential reference for the specialty and sustainable advancement of the coffee industry in comparable regions.
基金supported by the National Key Research and Development Program(No.2022YFC2807400)the National Natural Science Foundation of China(Nos.12265003 and 12205044)。
文摘Aerial surveys are dynamic and continuous processes,and there are different height distributions of the ground in the measurement area,which leads to problems such as overlapping measurement areas and inaccurate altitude correction during the survey process.Commonly used terrain correction methods are based on the concept of finite elementization of ground surface radioactive sources,using GPS coordinates,radar altitude,and ground elevation distribution information from aerial surveys,combined with the sourceless efficiency calibration method to construct a response matrix,which is then inverted for surface nuclide content.However,most of the sourceless efficiency calibration methods used are numerical calculations that consider the body detector as a point detector and do not consider the changes in intrinsic detection efficiency under different incident directions of gamma rays.Therefore,when the altitude of the measurement area varies significantly or the flight altitude of the aerial survey is relatively low,such sourceless efficiency calibration method calculations tend to have a large bias,which affects the accuracy of the terrain correction.To address the above problems,this study employs a novel sourceless efficiency calibration method based on the Boolean operation of the ray deposition process and simplifies the traditional body source measurement model to a surface source measurement model to achieve fast and accurate efficiency calibration.Then,through the discretization of the measurement process,the static measurement process is superposed as equivalent to the dynamic measurement process,and the dynamic measurement response matrix is built and optimized based on the calibration method.Finally,the PSO-MLEM algorithm was used to solve the dynamic measurement response matrix to achieve dynamic terrain correction of aerial survey data.Analysis of the Baiyun'ebo test area revealed that,after applying dynamic terrain correction,the inverted anomalies in uranium(eU),thorium(eTh),and potassium(K)concentrations were closer to ground measurements(within 5.72%-30.79%)and exhibited clearer anomaly boundaries compared to traditional height-based corrections.However,owing to the inherent statistical fluctuations and characteristics of matrix inversion,higher measurement values tend to absorb lower ones,potentially enlarging the anomalous regions.Nevertheless,the highanomaly regions after inversion largely coincided with the ground truth validation,demonstrating that the proposed method can effectively correct airborne gamma spectrometry data.
基金support of the National Natural Science Foundation of China(No.12172023)。
文摘According to the Mindlin plate theory and the first-order piston theory,this work obtains accurate closed-form eigensolutions for the flutter problem of three-dimensional(3D)rectangular laminated panels.The governing differential equations are derived by the Hamilton's variational principle,and then solved by the iterative Separation-of-Variable(i SOV)method,which are applicable to arbitrary combinations of homogeneous Boundary Conditions(BCs).However,only the simply-support,clamped and cantilever panels are considered in this work for the sake of clarity.With the closed-form eigensolutions,the flutter frequency,flutter mode and flutter boundary are presented,and the effect of shear deformation and aerodynamic damping on flutter frequencies is investigated.Besides,the relation between panel energy and the work of aerodynamic load is discussed.The numerical comparisons reveal the following.(A)The flutter eigenvalues obtained by the present method are accurate,validated by the Finite Element Method(FEM)and the Galerkin method.(B)When the span-chord ratio is larger than 3,simplifying a 3D panel to 2D(two-dimensional)panel is reasonable and the relative differences of the flutter points predicted by the two models are less than one percent.(C)The reciprocal relationship between the mechanical energy of the panel and the work done by aerodynamic load is verified by using the present flutter eigenvalues and modes,further indicating the high accuracy of the present solutions.(D)The coupling of shear deformation and aerodynamic damping prevents frequency coalescing.
基金funded by the National Natural Science Foundation of China(Grant No.12227801).
文摘This paper proposes a state-of-the-art three-dimensional Voronoi cell finite element method(3D VCFEM)aimed at investigating the mechanical properties of particle-reinforced composites(PRCs)in space under different microstructural properties.Firstly,the modified residual energy generalized function of 3D VCFEM was proposed by applying the hybrid stress element method,and the element format of the 3D Voronoi element was constructed.On this basis,the interaction between the matrix and the inclusions was considered,and the higher-order stress function including the interaction stress term was constructed.Secondly,to solve the difficulty of integrating easily due to the complexity and irregularity of the integration region in space,Delaunay tetrahedra were introduced within the 3D Voronoi element for mesh refinement.It simplified the integration process.Finally,to verify the accuracy and efficiency of the 3D VCFEM model,comparative models of 3D VCFENM and FEM were established for analysis and discussion.The stress field and strain field were compared and analyzed for the first time.An example was also given for the presence of a large number of randomly distributed inclusion particles.The results showed that under the same accuracy,3D VCFEM had the advantages of convenient mesh delineation and high computational efficiency compared with FEM,which provided a new way of thinking to analyze the actual PCRs.
文摘针对弱纹理和变光照环境下基于点特征的视觉SLAM(simultaneous localization and mapping)算法轨迹漂移的问题,提出了一种基于改进自适应阈值ELSED算法(Adaptive-ELSED)的快速点线融合双目视觉SLAM算法。通过在ELSED算法中添加自适应阈值矩阵,动态调整不同光照条件下梯度阈值,并使用长度抑制和短线合并策略,提高线特征的质量。利用基于双目几何约束和图像结构相似性(SSIM)进行快速线段特征三角化。基于历史位姿及误差分析获取初始位姿,通过自适应因子实现光束法平差过程中点线特征的更有效融合。实验结果表明,所提算法在提高线特征质量的同时,耗时仅为LSD算法的50%,线特征匹配速度较传统LBD算法提升67%,挑战性场景下轨迹误差较ORB-SLAM3降低62.2%,系统的平均跟踪帧率为27帧/s,在保证系统实时性的同时,显著提升了系统在弱纹理、变光照环境下的精度和鲁棒性。
文摘目前多数视觉即时定位与地图构建(simultaneous localization and mapping,SLAM)方案都是通过提取环境中的特征点来估计位姿,在纹理较少的弱纹理环境中仍存在较大的局限性。为此,在SLAM系统中引入线特征以保证系统能在弱纹理场景中稳定运行。但目前融合点线的视觉SLAM方案存在实时性和精度不足的问题,因此提出基于改进点线特征融合的的视觉惯性SLAM算法。算法前端中,采用FAST(features from accelerated segment test)角点作为特征点提取算法,对ELSED(enhanced line segment detection)算法进行增加短线合并、梯度阈值参数调整,并将四叉树均匀化分布特征点扩展到点线特征,提出改进的点线特征提取算法,减少高纹理区域和特征分布不均的情况对系统精度的影响。对点线特征的跟踪,均采用改进型光流法追踪,将惯性测量单元(inertial measured unit,IMU)得到的位姿信息和已知的特征点深度计算光流法的初值,代替原本的图像金字塔迭代过程,从而节省计算资源,满足系统的实时性。最后,在实际场景中将该系统与优秀的开源方案进行实验对比,验证了所提算法的实时性和精确性。实验表明,本算法可为工业巡检、仓储物流等场景下的机器人提供高鲁棒性定位解决方案,具有显著的产业应用前景。
文摘针对动态场景下视觉SLAM(Simultaneous Localization and Mapping)系统中深度学习分割网络实时性不足,以及相机非期望运动导致位姿估计偏差的问题,提出一种基于跨域掩膜分割的视觉SLAM算法.该算法采用轻量化YOLO-fastest网络结合背景减除法实现运动物体检测,利用深度图结合深度阈值分割构建跨域掩膜分割机制,并设计相机运动几何校正策略补偿检测框坐标误差,在实现运动物体分割的同时提升处理速度.为优化特征点利用率,采用金字塔光流对动态特征点进行帧间连续跟踪与更新,同时确保仅由静态特征点参与位姿估计过程.在TUM数据集上进行系统性评估,实验结果表明,相比于ORB-SLAM3算法,该算法的绝对位姿误差平均降幅达97.1%,与使用深度学习分割网络的DynaSLAM和DS-SLAM的动态SLAM算法相比,其单帧跟踪时间大幅减少,在精度与效率之间实现了更好的平衡.
