Analysis of damage localization for ductile metal in process of shear band propagation

1 Introduction Shear localization is an important and often dominating deformation and failure mechanism for Ti and Ti alloy in dynamic loadings[1—10]. The eventual outcome of localized deformation is ductile rupture and material separation. Shear locali…     

PolSAR快速贝叶斯非局部均值相干斑抑制方法

从单极化合成孔径雷达(SAR)贝叶斯非局部均值算法出发,推导了极化相干矩阵在复Wishart分布下的块相似性度量函数,给出了无先验知识下的极化SAR贝叶斯非局部均值模型,并采用积分图实现了该算法的快速计算.最后,通过机载合成孔径雷达实测旧金山地区的极化SAR数据进行了验证.实验结果表明,文中方法能够有效抑制相干斑的同时,保持了极化特征,并大幅提升了运算效率.     

煤矿视频监控图像的改进非局部均值滤波算法

针对井下光线较差、粉尘大而导致视频监控图像清晰度不佳的问题,提出了一种改进非局部均值滤波算法。首先采用Log边缘检测算子对图像进行边缘提取,获得边缘和非边缘图像;然后分别从相似图像块获取方法以及权重值计算方法2个方面对非局部均值滤波算法进行改进,用于去除非边缘图像中的噪声点;最后将边缘图像与滤波后的非边缘图像进行融合。分别采用该算法与中值滤波算法、均值滤波算法、非局部均值滤波算法对现场采集的图像进行测试,结果表明该算法的图像处理效果明显优于其他算法。     

基于非局部算法的序列图像超分辨率重构

提出了一种基于非局部算法的多帧图像超分辨率重构算法,该方法无需进行图像校正。为克服传统图像复原算法基于图像局部点领域的影响,指出可以使用非局部去噪模型的优越边缘保持性和去噪性来重构高分辨率图像。实验证明,该算法在低信噪比情况下,可以取得较好结果,有效解决了低信噪比条件下图像复原的一个难点。     

基于轻量级图卷积的人体骨架动作识别方法

视频中的人体动作识别在计算机视觉领域得到广泛关注,基于人体骨架的动作识别方法可以明确地表现人体动作,因此已逐渐成为该领域的重要研究方向之一。针对多数主流人体动作识别方法网络参数量大、计算复杂度高等问题,设计一种融合多流数据的轻量级图卷积网络,并将其应用于人体骨架动作识别任务。在数据预处理阶段,利用多流数据融合方法对4种特征数据流进行融合,通过一次训练就可得到最优结果,从而降低网络参数量。设计基于图卷积网络的非局部网络模块,以捕获图像的全局信息从而提高动作识别准确率。在此基础上,设计空间Ghost图卷积模块和时间Ghost图卷积模块,从网络结构上进一步降低网络参数量。在动作识别数据集NTU60 RGB+D和NTU120 RGB+D上进行实验,结果表明,与近年主流动作识别方法ST-GCN、2s AS-GCN、2s AGCN等相比,基于该轻量级图卷积网络的人体骨架动作识别方法在保持较低网络参数量的情况下能够取得较高的识别准确率。     

Non-local line method for notched elements with use of effective length calculated in an elasto-plastic condition

The paper presents a non-local line method used to the fatigue life calculation of notched elements. The presented method is based on the concept of an effective length which determines the size of the equivalent fatigue zone. Effective values of normal stress calculated in the critical plane with a weight function were applied when determining the equivalent fatigue zone. Simulation studies were performed for two types of steel and two types of loading. Five different series of tests and simulations were used. Experimental studies were carried out for 40 HM-T and EA4T steels. These materials are used in railway industry, including the manufacturing of coupling bars. The notched test specimens contained notches with a tip radius of 0.2, 0.5, 0.8 and 1 mm. Stress calculations were performed using the finite element method by adopting cyclic material properties described by the model of a multi-linear hardening. Non-local calculations were performed in a defined critical plane for normal stress distribution and a weight function. As a result, the function of variation of the effective length depending on the loading level and geometry of the notch has been determined.     

改进权值非局部均值超声图像去噪

目的 超声图像斑点噪声会影响诊断的准确性和可靠性。通过分析超声图像斑点噪声统计模型,结合非局部均值滤波算法,提出一种基于超声斑点噪声模型的改进权值非局部均值（NLM）滤波算法。方法 算法针对超声图像灰度信息对图像进行预处理,利用超声图像斑点噪声模型改进传统NLM算法的权值计算函数,基于图像特征确定最优采样间隔进行下采样,利用改进后的权值计算函数对图像进行NLM去噪处理。结果 分别采用人工合成与真实超声图像对本文算法性能进行测试,并与传统非局部均值滤波算法、非局部总变分（NLTV）等算法进行去噪效果比较,同时采用均方误差、峰值信噪比和平均结构相似性作为滤波算法性能的客观评价指标。本文算法能快速完成超声图像的去噪处理,峰值信噪比较其他算法可以提高0.2 dB以上,可以降低均方误差,提高平均结构相似性,缩短处理时间,并得到较好的图像质量和视觉效果。结论 根据超声图像斑点噪声模型对NLM算法的权值计算函数进行优化,使得NLM图像滤波算法能更好地适用于超声图像的去噪,基于超声斑点噪声模型的改进权值NLM算法相较于其他算法,滤波效果更佳,适合超声图像去噪。     

基于非局部均值的单帧图像超分辨率重建算法

为了解决单帧低分辨率图像获得高分辨率图像的问题,提出了一种基于非局部均值滤波的单帧图像超分辨率算法,将图像超分辨率重建视为反问题,建立正则化模型,充分考虑图像的局部结构信息和自然图像中不同尺度的相似性冗余,加入非局部滤波.实验结果表明,文中算法从单帧图像重建的图像边缘轮廓和纹理较传统算法清楚,有效抑制了人工伪影,同时对噪声具有鲁棒性.在视觉效果及峰值信噪比上都取得良好的结果.     

Non-Local Theory Solution for an Anti-Plane Shear Permeable Crack in Functionally Graded Piezoelectric Materials

In this paper, the non-local theory solution of a Griffith crack in functionally graded piezoelectric materials under the anti-plane shear loading is obtained for the permeable electric boundary conditions, in which the material properties vary exponentially with coordinate parallel to the crack. The present problem can be solved by using the Fourier transform and the technique of dual integral equation, in which the unknown variable is the jump of displacement across the crack surfaces, not the dislocation density function. To solve the dual integral equations, the jump of the displacement across the crack surfaces is directly expanded in a series of Jacobi polynomials. From the solution of the present paper, it is found that no stress and electric displacement singularities are present near the crack tips. The stress fields are finite near the crack tips, thus allows us to use the maximum stress as a fracture criterion. The finite stresses and the electric displacements at the crack tips depend on the crack length, the functionally graded parameter and the lattice parameter of the materials, respectively. On the other hand, the angular variations of the strain energy density function are examined to associate their stationary value with locations of possible fracture initiation.     

A multi-spectral non-local method for retrieval of boundary layer cloud properties from optical remote sensing data

A multi-spectral non-local (MSN) method is developed for advanced retrieval of boundary layer cloud properties from remote sensing data, as an alternative to the independent pixel approximation (IPA) method. The non-local method uses data at both the target pixel and neighboring pixels to retrieve cloud properties such as pixel-averaged cloud optical thickness and effective droplet radius. Radiance data to be observed from space were simulated by a three-dimensional (3D) radiation model and a stochastic boundary layer cloud model with two-dimensional (horizontal and vertical) variability in cloud liquid water and effective radius. An adiabatic assumption is used for each cloud column to model the geometrical thickness and vertical profiles of cloud liquid water content and effective droplet radius, neglecting drizzle and cloud brokenness for simplicity. The dependence of radiative smoothing and roughening on horizontal scale, optical thickness and single scattering albedo are investigated. Then, retrieval methods using 250-m horizontal resolution data onboard new generation satellites are discussed. The regression model for the MSN method was trained based on datasets from numerical simulations. The training was performed with respect to various domain averages of optical thickness and effective radius, because smoothing and roughening effects are strongly dependent on the two variables. Retrieval accuracy is discussed here with datasets independent of those used in the training, towards assessing the generality of the technique. It is demonstrated that retrieval accuracy of cloud optical thickness, which is often retrieved from single-spectral visible-wavelength data, is improved the most using neighboring pixel data and secondly using multi-spectral data, and ideally with both. When the IPA retrieval method is applied to optical thickness and effective radius, the root-mean-square relative errors can be 15-90%, depending on solar and view directions. In contrast, the MSN method has errors of 4-10%, which is smaller than IPA by a factor of 2-10. It is also suggested that the accuracy of the MSN method is insensitive to some assumptions in the inhomogeneous cloud input data used to train the regression model.