铁路测量中坐标系的建立与转换

在铁路测量中,长度投影变形要求小于2．5cm／km。但是由于铁路为典型的线性工程,通常横跨多个投影带,因此采用国家标准3。带难以满足铁路测量精度要求,本文通过分析高斯投影长度变形,提出分段建立独立坐标系的方法,控制长度投影变形,满足精度要求,最后介绍利用GlobalMapper软件实现两个独立坐标系的转换。     

A 3-dimensional data model for visualizing cloverleaf junction in a city model

The research work has been seldom done about cloverleaf junction expression in a 3-dimensional city model (3DCM). The main reason is that the cloverleaf junction is often in a complex and enormous construction. Its main body is bestraddle in air, and has aerial intersections between its parts. This complex feature made cloverleaf junction quite different from buildings and terrain, therefore, it is difficult to express this kind of spatial objects in the same way as for buildings and terrain. In this paper, authors analyze spatial characteristics of cloverleaf junction, propose an all-constraint points TIN algorithm to partition cloverleaf junction road surface, and develop a method to visualize cloverleaf junction road, surface using TIN. In order to manage cloverleaf junction data efficiently, the authors also analyzed the mechanism of 3DCM data management, extended BLOB type in relational database, and combined R-tree index to manage 3D spatial data. Based on this extension, an appropriate data structure for cloverleaf junction in 3DCM is proposed.     

Voronoi邻近关系支持下的点模式趋同提取方法

点模式及其趋同研究是揭示地学现象的产生、发展与演变,量化空间相似性分布、诠释空间分布成因的重要方式。目前,点模式研究侧重于已知频率与随机分布的一元独立性检验、距离测度下单观测值的二元相关性分析,而针对集聚过程相关性,空间拓扑与非拓扑邻近、综合多观测值的点模式趋同量化研究顾及不足。据此,以空间邻近性聚类、局部相关的多指标评价为切入点,本文提出了一种Voronoi邻近关系支持下的点模式趋同提取方法。首先,以Voronoi邻近相关表集聚算法剖分出空间独立性点模式;其次,依据Voronoi邻近关系指数测度、样本分布均值与分布方差的趋同假设,使用拉普拉斯平滑算子评价趋同度;最后,依据λ截矩阵,提取出Voronoi邻近、非Voronoi邻近关系支持下的强趋同点模式。试验以云南省腾冲市居民点数据为算例,经与点模式构建的聚类方法对比、趋同度计算与强趋同提取,验证了该方法的可行性与有效性。     

大跨钢桁梁形变对轨道平顺性的影响

针对由于大跨钢桁梁形变导致其上设置的轨道控制点(CPIII)空间位置的变化,进而导致轨道平顺性的测量结果受到影响的问题,该文从轨道维护角度出发,探讨大跨钢桁梁形变对轨道测量及平顺性影响规律。通过模拟实验对大跨钢桁梁形变引起的自由设站坐标、钢轨几何位置测量值以及轨道平顺性指标3方面的影响进行了深入讨论,结果表明:对于直线段大跨钢桁梁部分的轨道平顺性影响较小,对钢桁梁与两端混凝土梁连接处的轨道平顺性影响较大。     

基于TM30的立式储油罐变形分析

通过对某一大型的石油储油罐进行实地观测,阐述了采用徕卡TM30对大型储油罐进行变形观测的工作原理及简单操作流程。用拟合的方法拟合出基准圆及其他每一圈板的圆心,编程实现观测数据的自动化处理,求解出需要的几何参数,节约了工作成本并提高了效率。最后对油罐的变形程度做出分析和评价。     

Point grid map: a new type of thematic map for statistical data associated with geographic points

ABSTRACT

Social, economic, and environmental statistical data associated with geographic points are currently globally available in large amounts. When conventional thematic maps, such as proportional symbol maps or point diagram maps, are used to represent these data, the maps appear cluttered if the point data volumes are relatively large or cover a relatively dense region. To overcome these limitations, we propose a new type of thematic map for statistical data associated with geographic points: the point grid map. In a point grid map, an input point data set is transformed into a grid in which each point is represented by a square grid cell of equal size while preserving the relative position of each point, which leads to a clear and uncluttered appearance, and the grid cells can be shaded or patterned with symbols or diagrams according to the attributes of the points. We present an algorithm to construct a point grid map and test it with several simulated and real data sets. Furthermore, we present some variants of the point grid map.     

地面三维激光扫描技术在变电站精细测量中的应用

变电站是重要的电力设施,对其进行测绘采集是三维建模与可视化、运行维护、管理、异常监控等工作的基础,但其中构筑物具有复杂、结构异形等特点。本文利用三维激光扫描技术获取点云数据,对变电站进行精细测量。提出了基于空间区域复杂度的划分（如将测区划分为均匀分布区、紧密排列区、气体绝缘封闭组合电器（GIS）区、过渡区）方法,并以新疆亚中变电站为例展示了该方法的应用,最终实现了变电站的三维建模与可视化。     

A Comparative Study of Various Supervised Learning Approaches to Selective Omission in a Road Network

Selective omission is necessary for road network generalisation. This study investigates the use of supervised learning approaches for selective omission in a road network. To be specific, at first, the properties to measure the importance of a road in the network are viewed as input attributes, and the decision of such a road is retained or not at a specific scale is viewed as an output class; then, a number of samples with known input and output are used to train a classifier; finally, this classifier can be used to determine whether other roads to be retained or not. In this study, a total of nine supervised learning approaches, i.e., ID3, C4·5, CRT, Random Tree, support vector machine (SVM), naive Bayes (NB), K-nearest neighbour (KNN), multilayer perception (MP) and binary logistic regression (BLR), are applied to three road networks for selective omission. The performances of these approaches are evaluated by both quantitative assessment and visual inception. Results show that: (1) in most cases, these approaches are effective and their classification accuracy is between 70% and 90%; (2) most of these approaches have similar performances, and they do not have any statistically significant difference; (3) but sometimes, ID3 and BLR performs significantly better than NB and SVM; NB and KNN perform significantly worse than MP, SVM and BLR.     

一种基于Helmert方差分量估计的Vondrak滤波方法

从基于Helmert方差分量估计的Vondrak滤波方法(简称HVF法)的基本假设入手,介绍了HVF方法,该方法能够在未知拟合函数的情况下,通过自动选择合理的平滑因子控制数据平滑的程度,对时序数据序列进行合理平滑,最大限度的削弱数据序列中的随机误差,将信号与噪声合理分离.     

GPS应用于高空施工机械安全监控

结合小湾水电站建设施工情况,利用实地采集的GPS定位数据,探讨使用GPS实时动态定位技术构建高空施工机械安全监控系统的实现原理和可行性,同时介绍构成系统的各个模块及其功能,给出有效地实施高空施工机械安全运行监控的实用方法。