基于有限元方法的单搭接接头可靠性设计

将概率统计的设计观念引入单搭接粘接接头,通过有限元分析方法分析了对粘接接头力学性能影响较大的因素,并在抽样100次的情况下,分析了单搭接粘接接头失效的概率。结果表明,该模型可以有效地反映接头的实际情况,为粘接结构的可靠度设计提供了依据。     

中国图像工程：2013

该文是关于中国图像工程的年度文献综述系列之十九。为了使国内广大从事图像工程研究和图像技术应用的科技人员能够较全面地了解国内图像工程研究和发展的现状,并能够方便地查询有关文献,现从2013年在国内15种有关图像工程重要中文期刊的共140期上所发表的2986篇学术研究和技术应用文献中,选取出716篇属于图像工程领域的文献,并根据各文献的主要内容将其分别归入图像处理,图像分析,图像理解,技术应用和综述5个大类,然后进一步分入23个专业小类（与前8年相同）。在此基础上还分别进行了各期刊各类文献的统计和分析。根据统计分析结果可看到我国图像工程在2013年许多新进展的情况。     

Local adaptive segmentation algorithm for 3-D medical image based on robust feature statistics

Medical image segmentation is of pivotal importance in computer-aided clinical diagnosis. Many factors, including noises, bias field effect, local volume effect, as well as tissue movement may affect the med- ical image, thus causing blurring or uneven characteristics when forming a picture. Such quality defects will inevitably impair the gray-scale difference between adjacent tissues and lead to insufficient segmentation or even leakage during tissue or organ segmentation. In the present investigation, a local adaptive segmentation algorithm for 3-D medical image based on robust feature statistics （LARFS） was proposed. By combining segmentation algorithm principles for traditional region growing （RG） and robust feature statistics （RFS）, the location and neighborhood image information of input seed point can be comprehensively analyzed by LARFS. Results show that, for different segmentation objects, under controlling the input parameter of growing factor within certain range, LARFS segmentation algorithm can adapt well to the regional geometric shape. And be- cause the robust feature statistics is applied in the contour evolution process, LARFS algorithm is not sensitive to noises and not easily influenced by image contrast and object topology. Hence, the leakage and excessive segmentation effects are ameliorated with a smooth edge, and the accuracy can be controlled within the effective error range.     

Predicting cetane numbers of n-alcohols and methyl esters from their physical properties

Cetane numbers (C#) for the homologous series of straight-chain, saturated n-alcohols, C₅−C₁₂ and C₁₄, were determined according to ASTM D 613. Measured C# ranged from 18.2–80.8 and increased linearly with carbon number (CN). Regression analyses developed equations that related various physical properties or molecular characteristics of these alcohols to calculated C#. The degree of relationship between measured and calculated C# was expressed as R². The decreasing order of the precision with which these properties correlated with C# was: boiling point (bp)>melting point (mp)>CN>heat of combustion (HG)>refractive index (n²⁰ _D)>density (d). This ranking was based upon R² (0.99–0.96) and the Average % error (2.8–7.2%). C# were also determined for straight-chain homologs of saturated methyl esters with CN of 6, 10, 12, 14, 16 and 18. C# ranged from 18.0–75.6 and increased curvilinearly with CN. Equations were also developed that related physical properties of these esters to C#. The precision with which these properties correlated with C# was: bp>viscosity (V)>heat of vaporization (HV)>HG>CN>surface tension (ST)>mp>n²⁰ _D>d. R² ranged from 0.99 for bp to 0.98 for d. Equations for the alcohols were linear or quadratic, while equations for the esters were linear, quadratic or cubic based upon statistical considerations that included a Student’s t-test. With related physical properties and these equations, accurate predictions of C# can be made for saturated n-alcohols and methyl esters.     

基于规范变量残差的化工过程微小故障检测与诊断

微小故障因其幅值低而易被噪声和过程扰动所掩盖,并且会随时间慢慢演变成过程中的严重故障.因此,微小故障的检测和诊断变得越来越重要.为了更有效地监测和诊断微小故障,提出了基于规范变量残差的化工过程微小故障检测和诊断方法.首先,对Hankel矩阵执行奇异值分解来获得主元和残差空间并根据过去和未来数据的差异,求得两个不同的规范变量残差d_1, d_2.其次,考虑数据的时间序列特性,提出了基于规范变量残差的两个加权平均统计量W_(D1), W_(D2)及其控制限,进行故障检测;然后,计算出各个统计量的归一化贡献并绘制二维贡献图,进行故障诊断.最后,在连续搅拌釜式反应器(CSTR)过程中进行两种微小故障的应用研究.结果表明,与传统的统计量T~2,Q以及规范变量差异分析(CVDA)中统计量D相比,基于规范变量残差的加权平均统计量W_(D1), W_(D2)不仅能够及时检测到微小故障,而且在故障检测率和诊断率方面,均有不同程度的提高.     

基于变分模态分解和高阶统计量的梯级故障诊断研究

自动扶梯是地铁车站内必不可少的大型公共交通设备,一旦发生故障,小则影响运营,大则引发安全事故;梯级作为自动扶梯的重要结构部位,其固定螺栓松动必然会导致自动扶梯运行异常;针对梯级振动信号故障特征难以提取的问题,提出了变分模态分解(VMD)和高阶统计量(HOS)联合来对自动扶梯故障特征提取;该方法首先对原始振动信号进行VMD分解,得到K个固有模态分量(IMF);然后对主IMF分量进行奇异值分解(SVD)降噪,对去噪后的主IMF分量进行重构得到新的信号;最后通过高阶统计量对新的信号故障特征提取,并利用随机森林分类算法对三类不同的振动信号样本进行分类识别,确定梯级振动故障类型;实验结果表明,该方法可以有效地提取故障特征,实现故障诊断与分类。     

基于二次虚拟扩展的高分辨率波达方向估计方法

为进一步提高天线阵波达方向估计的分辨率,在四阶量多重信号分类方法的基础上,提出一种高分辨率的波达方向估计方法.利用阵列接收数据的四阶矩量进行虚拟阵列扩展,再利用阵列接收数据的共轭进行虚拟阵列扩展,实现二次虚拟扩展;将扩展后的阵列导向矢量和协方差矩阵用于波达方向估计,与原阵列导向矢量和协方差矩阵相比,相当于构造了更多的虚拟阵元,并扩展了阵列的孔径.仿真结果表明:与四阶量多重信号分类等波达方向估计方法相比,所提出的方法在波达方向估计中成功概率更高,均方误差更低,具有更高的分辨率.所提方法通过二次虚拟扩展,构造了更多的虚拟阵元,有效地提高了天线阵波达方向估计的分辨率.     

一种基于MPS的图像重建方法

提出了一种利用多点地质统计法实现图像重建的方法.由于传统基于线性降维的多点地质统计法不能有效处理非线性数据,因此引入等距特征映射以实现非线性数据的降维,并利用条件数据以提高重建图像的质量.实验证明,该方法有利于提高图像重建的有效性.     

基于NASA观测数据的风电出力时空分布及波动特性分析

为克服实际风电场运行数据难以获取的问题,提出一种基于历史风速的风资源评估方法。首先,基于美国NASA(National aeronautics and space administration)数据中心获取风速数据,并利用假想风电机组模型转化为风机出力时间序列;然后,通过对时间序列的统计分析,计算期望、半载概率等指标评估风电出力的时空分布特性;最后,通过计算风电出力方差和分析相邻峰谷点差值概率分布规律分析风电出力的波动特性。所提方法能够同时考虑风资源自然特性和风电机组特性,且能对风电波动特性提供定量描述。利用所提方法对山东省风资源的评估结果表明:山东省可利用风能资源随地区、季节和昼夜的变化呈现出明显规律。