一种图像校正的偏振光罗盘系统的研究

导航传感器在探险、应急、精确制导武器、船舶、航空器导航和定位系统中起着关键作用。针对偏振光罗盘在倾斜状态下误差较大的问题,提出了一种利用加速度计和陀螺仪对偏振光罗盘进行图像校正的方法,设计了一种基于陀螺仪校正的偏振光罗盘系统。首先利用加速度计和陀螺仪计算得到载体姿态角,对偏振光图像数据进行图像校正,采用Stokes矢量法解算大气偏振模式分布,进而提取导航特征点,最后对特征点进行拟合解算出航向角信息。并且进行了静态和动态测试实验,实验结果表明,该算法能够有效的对偏振光罗盘姿态变化引起的误差进行补偿,可以将偏振光罗盘的航向角测量误差控制在1.86°之内,平均误差为0.09°。     

图像分类中基于分类矢量量化的视觉词袋模型

特征表示是图像识别和分类的基础，视觉词袋是一种图像的特征表示方法。分析现有视觉词典构建方法的不足，提出一种新的视觉词典构建方法。首先利用梯度方差把特征矢量分为光滑类和边缘类，然后分别针对不同类别的特征矢量进行视觉词典的构建，最后根据两类视觉词典生成视觉词袋。图像分类实验表明，提出的新方法能提高分类准确率。     

Experimental investigation of far-field human cough airflows from healthy and influenza-infected subjects

Seasonal influenza epidemics have been responsible for causing increased economic expenditures and many deaths worldwide. Evidence exists to support the claim that the virus can be spread through the air, but the relative significance of airborne transmission has not been well defined. Particle image velocimetry (PIV) and hot-wire anemometry (HWA) measurements were conducted at 1 m away from the mouth of human subjects to develop a model for cough flow behavior at greater distances from the mouth than were studied previously. Biological aerosol sampling was conducted to assess the risk of exposure to airborne viruses. Throughout the investigation, 77 experiments were conducted from 58 different subjects. From these subjects, 21 presented with influenza-like illness. Of these, 12 subjects had laboratory-confirmed respiratory infections. A model was developed for the cough centerline velocity magnitude time history. The experimental results were also used to validate computational fluid dynamics (CFD) models. The peak velocity observed at the cough jet center, averaged across all trials, was 1.2 m/s, and an average jet spread angle of θ = 24° was measured, similar to that of a steady free jet. No differences were observed in the velocity or turbulence characteristics between coughs from sick, convalescent, or healthy participants.     

Sparse non-convex Lp regularization for cone-beam X-ray luminescence computed tomography

Cone-beam X-ray luminescence computed tomography (CB-XLCT) is an attractive hybrid imaging modality, and it has the potential of monitoring the metabolic processes of nanophosphors-based drugs in vivo. However, the XLCT imaging suffers from a severe ill-posed problem. In this work, a sparse nonconvex L_p (0?p?L₁ regularization. Further, an iteratively reweighted split augmented lagrangian shrinkage algorithm (IRW_SALSA-L_p) was proposed to efficiently solve the non-convex L_p (0?p?p-values (1/16, 1/8, 1/4, 3/8, 1/2, 5/8, 3/4, 7/8) in both 3D digital mouse experiments and in vivo experiments. The results demonstrate that the proposed non-convex methods outperform L₂ and L₁ regularization in accurately recovering sparse targets in CB-XLCT. And among all the non-convex p-values, our L_p(1/4?p?相似文献   

镁合金网格壁板压弯成形数值模拟及实验研究

为探索镁合金整体壁板压弯成形的可行性,以及镁合金壁板压弯成形过程中金属的流动规律,对AZ31镁合金网格壁板压弯成形进行了数值模拟和实验研究。建立了有限元数值模拟的几何模型,采用有限元计算软件对AZ31镁合金网格壁板压弯成形过程进行了数值模拟研究,分析了镁合金网格壁板压弯成形中的温度场、应变场、应力场、破坏系数等的分布规律。确定了合适的AZ31镁合金壁板压弯成形工艺参数,并对镁合金网格壁板压弯成形进行了实验研究,获得了合格的镁合金网格壁板弯曲件,并分析了镁合金网格壁板成形件尺寸精度,模拟结果与实验结果相吻合,最大相对误差为16.7%。     

基于彩色图像处理的浮选尾煤灰分软测量研究

浮选尾煤灰分是浮选产品的一个重要指标。针对选煤厂浮选尾煤灰分多采用离线检测而无法实现在线准确测量，以及当前浮选软测量多采用单一的灰度图像从而导致软测量模型精度及适应性较差的问题，提出了一种基于彩色图像处理的浮选尾煤软测量方法，建立了基于最小二乘支持向量机(LSSVM)的浮选尾煤灰分软测量模型。模型以不同颜色空间的彩色特征、灰度均值以及浓度特征为输入变量，以尾煤灰分作为输出变量，采用粒子群优化算法对LSSVM模型参数进行优化。结果表明：所建立的尾煤灰分软测量模型可以较好地实现浮选尾矿灰分的在线预测，引入浮选尾矿图像的彩色特征可以提高尾煤图像分析的精度，预测精度达96.89%。研究成果在柳湾选煤厂现场应用，并取得了较好的尾矿灰分测量效果。     

自适应天牛须优化与K均值聚类的图像分割算法研究

在机器识别中,图像分割是重要的一个步骤,传统分割手段存在一定缺陷。针对传统K均值聚类分割的初始聚类中心敏感的缺陷进行了优化,利用自适应天牛须优化算法,避免了这一问题。通过实验结果表明,该算法(ABASK)对图像进行分割,既可以保证图像轮廓的分割,同时还可以更多地保留图像细节。     

煤矿地面轨道运输矿车自动避障技术研究

介绍了煤矿地面轨道运输矿车自动避障技术。首先介绍了基于雷达的矿车前方障碍物检测技术及其相关算法,然后详细介绍了基于机器视觉的矿车前方障碍物检测系统和常用的图像处理方法以及相关的算法,最后介绍了雷达和机器视觉融合的障碍物检测技术在煤矿地面轨道运输矿车自动避障过程中的应用。     

Reproducible,biocompatible medical materials from biologically derived polysaccharides: Processing and Characterization

Natural polysaccharides like chitosan and dextran have garnered considerable interest in biomedical applications due to their biocompatibility, biodegradability, and nontoxicity. Nonetheless, the development of a reproducible class of medical devices from these materials is challenging and has had limited success. Chitosan and dextran are inherently variable and synthesis using these materials is prone to inconsistencies. In this study, we put forward a robust product development regimen that allows these natural materials to be developed into a reproducible class of biomaterials. First, an array of validated characterization methods (Proton Nuclear Magnetic Resonance, titrations, Ultraviolet spectroscopy, Size Exclusion Chromatography—Multi-Angle Light Scattering, Size Exclusion Chromatography—Refractive Index, and proprietary methods) were developed that allowed rigorous specifications to be set for unprocessed chitosan and dextran, chitosan and dextran intermediates, and chemically modified materials—acrylated chitosan (aCHN) and oxidized dextran (oDEX). Second, a robust and reproducible synthesis scheme involving various in-process controls was developed to chemically modify the unprocessed polysaccharides. Third, purification methods to remove byproducts and low-molecular-weight impurities for both aCHN and oDEX were developed. The study presents a viable strategy for converting variable, natural materials into a reproducible class of biomaterials that can be applied in various biomedical applications. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48454.     

Mechanical and fracture investigation of magnesia refractories with acoustic emission-based method

In this study, the fracture behaviour of magnesia, magnesia chrome and magnesia spinel (MgAl₂O₄ and FeAl₂O₄) refractories under wedge splitting test are qualitatively and quantitatively investigated with the acoustic emission (AE) and digital image correlation (DIC). First of all, the concepts of characteristic widths are proposed for estimating the brittleness of refractory materials according to the shape of load-displacement curve and validated by their good correlation with the characteristic length. Besides, the AE data are analyzed with AE parameter-based approaches and offer new insight into the fracture behaviour of refractory materials, including the classification of the cracking events in grains and in matrix, the distinction between the tensile mode and shear mode damage, and the visualization of the fracture process zone development. It confirms that the pre-existing micro-crack networks in refractories are favourable for the brittleness reduction, which enhance their nonlinear fracture behaviour and thermal shock resistance.