X52K 铣床数控改造及设计

本文在Ｘ５２Ｋ铣床上采用ＣＮＣ数控系统和以步进电动机为驱动执行元件的开环控制，实现了Ｘ、Ｙ两坐标联动。     

A linearised pixel-swapping method for mapping rural linear land cover features from fine spatial resolution remotely sensed imagery

Accurate maps of rural linear land cover features, such as paths and hedgerows, would be useful to ecologists, conservation managers and land planning agencies. Such information might be used in a variety of applications (e.g., ecological, conservation and land management applications). Based on the phenomenon of spatial dependence, sub-pixel mapping techniques can be used to increase the spatial resolution of land cover maps produced from satellite sensor imagery and map such features with increased accuracy. Aerial photography with a spatial resolution of 0.25 m was acquired of the Christchurch area of Dorset, UK. The imagery was hard classified using a simple Mahalanobis distance classifier and the classification degraded to simulate land cover proportion images with spatial resolutions of 2.5 and 5 m. A simple pixel-swapping algorithm was then applied to each of the proportion images. Sub-pixels within pixels were swapped iteratively until the spatial correlation between neighbouring sub-pixels for the entire image was maximised. Visual inspection of the super-resolved output showed that prediction of the position and dimensions of hedgerows was comparable with the original imagery. The maps displayed an accuracy of 87%. To enhance the prediction of linear features within the super-resolved output, an anisotropic modelling component was added. The direction of the largest sums of proportions was calculated within a moving window at the pixel level. The orthogonal sum of proportions was used in estimating the anisotropy ratio. The direction and anisotropy ratio were then used to modify the pixel-swapping algorithm so as to increase the likelihood of creating linear features in the output map. The new linear pixel-swapping method led to an increase in the accuracy of mapping fine linear features of approximately 5% compared with the conventional pixel-swapping method.     

一种基于故障定位的配电网简化模型

针对农村配电网T接节点多而馈线终端单元(FTU)配置相对城网少的特点,对刘健教授提出的变结构耗散网络模型进行了反变换,消去大量没有安装FTU的T接节点,采用邻接表存储结构,结合算例进行了分析验证,可以更方便地进行故障定位,隔离故障区域。     

一种FBG载荷定位的温度补偿方法

在基于神经网络的光纤布喇格光栅(FBG)载荷定位系统中,由于测试区域内各个光栅所处的温度大致相同,如果将载荷定位系统中FBG的波长变化量两两组合,然后按一定的比例相减,将它们的差值作为神经网络的训练样本,则可抵消温度所引起的波长漂移,提高了在温度变化时FBG载荷定位系统的准确度。实验证实该方法可获得较准确的判定结果。     

Sub-pixel mapping and sub-pixel sharpening using neural network predicted wavelet coefficients

Sub-pixel mapping and sub-pixel sharpening are techniques for increasing the spatial resolution of sub-pixel image classifications. The proposed method makes use of wavelets and artificial neural networks. Wavelet multiresolution analysis facilitates the link between different resolution levels. In this work a higher resolution image is constructed after estimation of the detail wavelet coefficients with neural networks. Detail wavelet coefficients are used to synthesize the high-resolution approximation. The applied technique allows for both sub-pixel sharpening and sub-pixel mapping. An algorithm was developed on artificial imagery and tested on artificial as well as real synthetic imagery. The proposed method resulted in images with higher spatial resolution showing more spatial detail than the source imagery. Evaluation of the algorithm was performed both visually and quantitatively using established classification accuracy indices.     

坐标测量机测量短基准零件同轴度时误差过大问题的分析与解决

定性分析了三坐标测量机测量短基准零件同轴度时误差过大的原因。为控制测量误差 ,研制了可提高被测零件轴线与测量机坐标轴线平行性的装夹定位装置。     

基于RSSI修正的改进DV-Hop测距算法

针对DV-Hop算法测距误差受节点分布不均匀影响较大的问题和RSSI算法受环境因素影响较大的问题,提出了一种基于RSSI修正的改进型DV-Hop测距算法。该算法在保持DV-Hop算法环境适应性强的优点的同时,有效降低了由于节点分布不均而引起的测距误差,从而提高了定位精度。仿真结果表明该修正算法在不同的锚节点数和不同的通信半径下,均能够有效降低测距误差;同时该算法的定位精度与原DV-Hop算法以及另外3种以DV-Hop为基础的改进型算法相比均得以提高。     

一种基于数字签名的二值图像认证算法

为了实现对二值文本图像内容的全面保护,提出一种新的基于数字签名的二值图像认证算法。算法用数字签名实现对均匀块的认证,用归一化预处理实现对非均匀块的认证,通过两者联合认证来消除虚警。理论分析和实验结果表明,该算法仅需要附加极短的签名信息,就可以实现对二值文本图像内容的全面保护,在保证良好视觉效果的前提下,具有良好的窜改检测和窜改定位能力。     

基于空间矩的灰度边缘亚像元度量精度分析

灰度图像中边缘定位受采样密度限制，亚像元精度度量方法在需要高精度的应用中受到重视，要想知识到底需要多高的分辨率才能达到定精度指标，就有必要分析特征定位方法的最坏情况的精度，文中用分析和实验的方法给出了基于空间矩的边缘定位方法，对于边缘点，边缘直线以及直边缘区域的最坏情况定位精度分析。分析和讨论的结果不但可以用来确定已知形状位置估计的最大误差，而且还可用于对准的形状几何参数，以获得较高的精度。     

IP网络性能测量研究现状和进展

网络性能测量是网络测量领域的核心分支,是指遵照一定的方法和技术,利用软、硬件工具来测试、验证及表征网络性能指标的一系列活动总和,是量化网络性能指标,理解和认识网络行为最基本和最有效的手段,在网络建模、网络安全、网络管理和优化等诸多领域均有广泛应用,是计算机网络领域持续的研究热点之一.本文介绍了该领域的研究现状与进展,重点讨论了带宽、丢包和时延测量等方面的代表性算法,从算法的基本思想、关键技术、实现机理入手,剖析了突发性背景流的时间不确性和多跳网络路径下的空间不确定性对带宽测量的影响;丢包测量中应用流丢包与探测流丢包的区别与联系;时延测量中时钟偏差与时钟频差的相互作用关系等问题,并在此基础上对网络性能测量面临的挑战、发展趋势和进一步研究方向进行了讨论,希望能为该领域的研究者提供一些有益的启示.