Due to the nonlinearity of breathing crack, cracked structure under excitation of a single frequency always generates higher harmonic components. In this paper, operational deflection shape (ODS) at excitation frequen...Due to the nonlinearity of breathing crack, cracked structure under excitation of a single frequency always generates higher harmonic components. In this paper, operational deflection shape (ODS) at excitation frequency and its higher harmonic components are used to map the deflection pattern of cracked structure. While ODS is sensitive to local variation of structure in nature, a new concept named transmissibility of operational deflection shape (TODS) has been defined for crack localization using beam-like structure. The transmissibility indicates the energy transfer from basic frequency to higher frequency. Then, Teager energy operator (TEO) is employed as a singularity detector to reveal and characterize the features of TODS. Numerical and experimental analysis in cantilever beam show that TODS has strong sensitivity to crack and can locate the crack correctly.展开更多
A discriminative local shape descriptor plays an important role in various applications.In this paper,we present a novel deep learning framework that derives discriminative local descriptors for deformable 3D shapes.W...A discriminative local shape descriptor plays an important role in various applications.In this paper,we present a novel deep learning framework that derives discriminative local descriptors for deformable 3D shapes.We use local"geometry images"to encode the multi-scale local features of a point,via an intrinsic parameterization method based on geodesic polar coordinates.This new parameterization provides robust geometry images even for badly-shaped triangular meshes.Then a triplet network with shared architecture and parameters is used to perform deep metric learning;its aim is to distinguish between similar and dissimilar pairs of points.Additionally,a newly designed triplet loss function is minimized for improved,accurate training of the triplet network.To solve the dense correspondence problem,an efficient sampling approach is utilized to achieve a good compromise between training performance and descriptor quality.During testing,given a geometry image of a point of interest,our network outputs a discriminative local descriptor for it.Extensive testing of non-rigid dense shape matching on a variety of benchmarks demonstrates the superiority of the proposed descriptors over the state-of-the-art alternatives.展开更多
Thin-walled member is structurally superior to a construction member. However, by reason of complexity in structure the stress and the deformation to yield the cross section are complicated. Specially, in case thin-wa...Thin-walled member is structurally superior to a construction member. However, by reason of complexity in structure the stress and the deformation to yield the cross section are complicated. Specially, in case thin-walled members, such as thin-walled channel section columns, which are subjected to compressive force, these members produce the local buckling, distortional buckling and overall buckling. A number of experimental and theoretical investigations subjected to axial compressive force are generated for thin-walled channel section columns with triangle-shaped folded groove by Hancock [1] and with complex edge stiffeners and web stiffeners by Wang [2]. In case thin-walled channel section column with folded groove which is subjected to axial compressive force, it is cleared that the buckling mode shapes are ordinarily generated for local buckling mode shape of plate-panel composing cross section of member in short member aspect ratio and overall buckling mode shape as column and distortional buckling mode shape interacting between local buckling and overall buckling similarly normal thin-walled member. It is cleared analytically and experimentally that buckling strength and critical strength of thin-walled channel section column with folded groove can increase sharply in comparison with that of normal thin-walled member composing only plate-panel. In this paper a new cross section of shell-shaped curved groove [3] was proposed instead of the thin-walled lipped channel section column with triangle- and rectangle-shaped folded grooves used ordinarily, and therefore the comparison and the examination of buckling strength and buckling behavior were generated in the case of preparing triangle-shaped folded and shell-shaped curved grooves to web and flange of thin-walled channel section column. And then in order to investigate the buckling behavior on the thin-walled channel section column with folded and curved grooves, exact buckling strength and the buckling mode shapes are generated by using the transfer matrix method. The analytical local distortional and overall elastic buckling loads of thin-walled channel section column with folded and curved grooves can be obtained simultaneously by use of the transfer matrix method. Furthermore, a technique to estimate the buckling mode shapes of these members is also shown.展开更多
准确高效的麦粒计数对小麦育种和产量评估具有重要意义。传统人工计数方法费时费力且易出错。目前的自动计数方法主要基于二维图像处理技术,但在处理麦粒遮挡和获取立体形态特征方面存在局限。点云数据能够完整记录麦穗的三维几何结构,...准确高效的麦粒计数对小麦育种和产量评估具有重要意义。传统人工计数方法费时费力且易出错。目前的自动计数方法主要基于二维图像处理技术,但在处理麦粒遮挡和获取立体形态特征方面存在局限。点云数据能够完整记录麦穗的三维几何结构,为解决这些问题提供了新的思路。本文针对现有点云目标检测算法在处理密集分布麦粒时的不足,提出了一种改进的3DSSD网络用于麦穗点云中的麦粒检测与计数。该方法充分利用麦粒的形态学特征,设计了2个核心创新模块:一是提出局部形状感知采样策略(Local shape-aware sampling,LSAS),通过分析点云的局部几何结构来指导采样过程,有效缓解了传统最远点采样(Farthest point sampling,FPS)算法在密集目标场景下的特征退化问题;二是引入部件感知损失函数(Part-aware loss function,PALF),将麦粒建模为具有多个关键部位的目标,增强了网络对局部特征的感知能力。实验结果表明,改进后的方法在麦粒检测任务中AP@25达到72.68%,较基线3DSSD提升14.02%,计数任务MAE降至3.87,较3DSSD下降了85.54%,Recall提升至93.21%,从而在处理形态复杂、目标密集的麦穗点云时表现出显著优势。本研究为实现麦穗表型的快速、准确测量提供了新的技术方案,并成功地在马兰国家农业科技园区应用该方法。展开更多
文摘Due to the nonlinearity of breathing crack, cracked structure under excitation of a single frequency always generates higher harmonic components. In this paper, operational deflection shape (ODS) at excitation frequency and its higher harmonic components are used to map the deflection pattern of cracked structure. While ODS is sensitive to local variation of structure in nature, a new concept named transmissibility of operational deflection shape (TODS) has been defined for crack localization using beam-like structure. The transmissibility indicates the energy transfer from basic frequency to higher frequency. Then, Teager energy operator (TEO) is employed as a singularity detector to reveal and characterize the features of TODS. Numerical and experimental analysis in cantilever beam show that TODS has strong sensitivity to crack and can locate the crack correctly.
基金partially funded by the National Key R&D Program of China(2018YFB2100602)the National Natural Science Foundation of China(61802406,61772523,61702488)+2 种基金Beijing Natural Science Foundation(L182059)the CCF–Tencent Open Research Fund,Shenzhen Basic Research Program(JCYJ20180507182222355)the Open Project Program of the State Key Lab of CAD&CG(A2004)Zhejiang University.
文摘A discriminative local shape descriptor plays an important role in various applications.In this paper,we present a novel deep learning framework that derives discriminative local descriptors for deformable 3D shapes.We use local"geometry images"to encode the multi-scale local features of a point,via an intrinsic parameterization method based on geodesic polar coordinates.This new parameterization provides robust geometry images even for badly-shaped triangular meshes.Then a triplet network with shared architecture and parameters is used to perform deep metric learning;its aim is to distinguish between similar and dissimilar pairs of points.Additionally,a newly designed triplet loss function is minimized for improved,accurate training of the triplet network.To solve the dense correspondence problem,an efficient sampling approach is utilized to achieve a good compromise between training performance and descriptor quality.During testing,given a geometry image of a point of interest,our network outputs a discriminative local descriptor for it.Extensive testing of non-rigid dense shape matching on a variety of benchmarks demonstrates the superiority of the proposed descriptors over the state-of-the-art alternatives.
文摘Thin-walled member is structurally superior to a construction member. However, by reason of complexity in structure the stress and the deformation to yield the cross section are complicated. Specially, in case thin-walled members, such as thin-walled channel section columns, which are subjected to compressive force, these members produce the local buckling, distortional buckling and overall buckling. A number of experimental and theoretical investigations subjected to axial compressive force are generated for thin-walled channel section columns with triangle-shaped folded groove by Hancock [1] and with complex edge stiffeners and web stiffeners by Wang [2]. In case thin-walled channel section column with folded groove which is subjected to axial compressive force, it is cleared that the buckling mode shapes are ordinarily generated for local buckling mode shape of plate-panel composing cross section of member in short member aspect ratio and overall buckling mode shape as column and distortional buckling mode shape interacting between local buckling and overall buckling similarly normal thin-walled member. It is cleared analytically and experimentally that buckling strength and critical strength of thin-walled channel section column with folded groove can increase sharply in comparison with that of normal thin-walled member composing only plate-panel. In this paper a new cross section of shell-shaped curved groove [3] was proposed instead of the thin-walled lipped channel section column with triangle- and rectangle-shaped folded grooves used ordinarily, and therefore the comparison and the examination of buckling strength and buckling behavior were generated in the case of preparing triangle-shaped folded and shell-shaped curved grooves to web and flange of thin-walled channel section column. And then in order to investigate the buckling behavior on the thin-walled channel section column with folded and curved grooves, exact buckling strength and the buckling mode shapes are generated by using the transfer matrix method. The analytical local distortional and overall elastic buckling loads of thin-walled channel section column with folded and curved grooves can be obtained simultaneously by use of the transfer matrix method. Furthermore, a technique to estimate the buckling mode shapes of these members is also shown.
文摘准确高效的麦粒计数对小麦育种和产量评估具有重要意义。传统人工计数方法费时费力且易出错。目前的自动计数方法主要基于二维图像处理技术,但在处理麦粒遮挡和获取立体形态特征方面存在局限。点云数据能够完整记录麦穗的三维几何结构,为解决这些问题提供了新的思路。本文针对现有点云目标检测算法在处理密集分布麦粒时的不足,提出了一种改进的3DSSD网络用于麦穗点云中的麦粒检测与计数。该方法充分利用麦粒的形态学特征,设计了2个核心创新模块:一是提出局部形状感知采样策略(Local shape-aware sampling,LSAS),通过分析点云的局部几何结构来指导采样过程,有效缓解了传统最远点采样(Farthest point sampling,FPS)算法在密集目标场景下的特征退化问题;二是引入部件感知损失函数(Part-aware loss function,PALF),将麦粒建模为具有多个关键部位的目标,增强了网络对局部特征的感知能力。实验结果表明,改进后的方法在麦粒检测任务中AP@25达到72.68%,较基线3DSSD提升14.02%,计数任务MAE降至3.87,较3DSSD下降了85.54%,Recall提升至93.21%,从而在处理形态复杂、目标密集的麦穗点云时表现出显著优势。本研究为实现麦穗表型的快速、准确测量提供了新的技术方案,并成功地在马兰国家农业科技园区应用该方法。
