权的确定方法在核电施工控制测量中的应用探讨

在精密工程测量中,确定非同类观测值之间权的正确比例关系,对提高平差成果的质量具有重要意义。针对核电施工控制测量中,普遍采用高精度全站仪建立边角网、测量数据平差处理时按经验定权的现状,将Helmert验后方差定权引入核电测量数据处理,结合实际工程算例,阐明了二种定权方法之间的关系;克服了观测值先验精度与观测实际不符时定权不准确的不足;根据法方程及Helmert估算公式的特点,对工程中有效运用Helmert验后方差估计方法,进行了探讨。     

测量数据中粗差的探测与处理

利用巴尔达传统粗差检验方法检验剔除出数据中的粗差,并通过稳健估计方法处理含有粗差的数据以及传统平差方法处理剔除过粗差的数据,与加入粗差前的数据处理结果作对比,比较不同粗差处理方法的优缺点。经比较得出：在保证一定迭代计算次数的条件下,稳健估计能够达到抵抗粗差的目的;巴尔达粗差探测在数据中只含有一个粗差的情况下,与稳健估计相比,在满足一定精度要求的前提下,更能保证计算效率;在数据含有多个粗差的情况下,可利用稳健估计方法进行处理。     

向量加权平均值在桥梁控制网平差中的应用

桥梁控制网一般为边角网,传统的平差计算方法很难合理确定两类观测值的权比,因此直接影响到平差结果的正确性以及控制网的可靠性和粗差探测的效果.采用赫尔默特方差估计,可以较好地解决定权的问题,但需进行多个矩阵连乘后的求迹运算,既费机时,又占内存,过程繁琐.基于向量加权平均值,对桥梁控制网的平差计算提出了一种新方法,推导出了相关的计算公式.该方法有别于传统的计算方法,不需要考虑边长,角度二类观测值合理定权的问题,算例表明该方法占用内存小、计算过程简单明了.     

用于变形分析的L—X—1‘平差方法

为了直接处理含有粗差的变形观测数据，文献（１）提出了Ｌ－Ｘ－１平差模型，但这种Ｌ－Ｘ－平差模型解的唯一性较差，为此，本文提出了Ｌ－Ｘ－１‘平差方法，该方法与Ｌ－Ｘ－１平差比较，更容易得到唯一的平差结果，且计算起来方便。     

相关观测值的一次范数最小平差

本文从理论上推导了约束条件为参数平差的相关观测值的一次范数最小平差（Ｌ１平差）模型，并对不同的数学实例进行了试算。结果表明，Ｌ１平差具有较好的抗粗差能力。     

基于抗差Kalman滤波的精密单点定位

当精密单点定位的观测值含有异常数据时,Kalman滤波的精度将会降低。采用抗差Kalman滤波方法能够有效抑制观测异常,提高滤波的精度和可靠性。运用武汉国际GPS服务跟踪站数据对该方法进行了验证。结果表明,抗差Kalman滤波的精度比Kalman滤波的精度有一定程度提高,说明抗差Kalman滤波能够有效抑制观测异常。     

红外测距在信阳市燃气混气站场区断层水平位移监测中的应用

结合红外精密测距在信阳市燃气混气站场区稳定性研究中的应用,探讨了大气对红外测距的影响;在数据处理中采用了验后方差估计的自由网平差模型,使结果获得了亚毫米级的精度,并将F检验方法应用于变形分析中,得到了同观测结果相一致的结论,从而提高了工程岩土体稳定性定量评价的可信度。     

以坐标差为因子的导线平差

根据全站仪可以直接测量导线坐标的特点,以基本的测量平差知识为基础,探讨了以测量所得的坐标差为观测因子来建立平差函数模型,并依据间接平差原理进行平差的方法。平差结果和传统的平差方法的结果进行了比较,得出了这种平差方法的可行性。     

用于变形监测的最小二乘滤波数据处理

随着全站仪在测量工作中的广泛使用,以坐标为观测值的数据处理成为内业工作的主要内容。根据最小二乘滤波原理,将工程岩土体变形监测中所获得的坐标观测值及其他常规观测值进行联合平差。结果表明,滤波后变形点的点位精度最大可提高1.35 mm,最弱点亦提高0.94 mm,均明显高于直接观测结果,而且各类观测值之间所形成的约束条件进一步增强了平差结果的可靠性。     

基于选权迭代法的DEM粗差探测

在数字高程模型(DEM)数据采集和处理中,探测和剔除DEM数据中存在的粗差尤为重要。尝试把抗差估计的思想纳入到DEM粗差探测的算法中,探讨对模型误差,特别是粗差具有抵抗能力的基于稳健估计的选权迭代法的粗差探测方法。在数据中随机加入误差,通过对比最小二乘平差算法验证选权迭代法的有效性及稳健性。实验结果表明,基于稳健估计的选权迭代法具有良好的粗差探测能力。     

An Alternative Measure of the Reliability of Ordinary Kriging Estimates

This paper presents an interpolation variance as an alternative to the measure of the reliability of ordinary kriging estimates. Contrary to the traditional kriging variance, the interpolation variance is data-values dependent, variogram dependent, and a measure of local accuracy. Natural phenomena are not homogeneous; therefore, local variability as expressed through data values must be recognized for a correct assessment of uncertainty. The interpolation variance is simply the weighted average of the squared differences between data values and the retained estimate. Ordinary kriging or simple kriging variances are the expected values of interpolation variances; therefore, these traditional homoscedastic estimation variances cannot properly measure local data dispersion. More precisely, the interpolation variance is an estimate of the local conditional variance, when the ordinary kriging weights are interpreted as conditional probabilities associated to the n neighboring data. This interpretation is valid if, and only if, all ordinary kriging weights are positive or constrained to be such. Extensive tests illustrate that the interpolation variance is a useful alternative to the traditional kriging variance.     

应用Kriging方法研究格尔木河流域地下水位动态观测网的优化配置

地下水动态是水文地质研究的一个重要方面，如何获满足一定精度要求全面而合理的地下水位动态资料具有现实经济效益。本文研究格尔木河流域地下水位动态测网，通过选取理想的变差函，运有Ｋｒｉｇｉｎｇ方法进行地下水位的线性无偏最优估计和计算估计误差的标准差，结合给定的允许误差限评判地下水位动态观测网的配置是否合适，并提出调整现有观测网的方案     

地质统计学储量估算中块尺寸的合理选择

在矿产勘查、矿山设计、生产及管理等各阶段都需要进行资源储量估算的工作。地质统计学方法相对于传统储量估算方法具有明显优势,在资源储量估算中获得了广泛的应用。估值过程中单元块尺寸的合理选择对储量估算结果至关重要,然而,在以往实践中块尺寸通常根据经验或主观判断进行选择,缺乏科学依据。本文在总结前人工作及地质统计学资源储量估算经验的基础上,将块尺寸的选取问题明确地划分为勘探阶段和生产阶段。针对不同阶段的特点,重点讨论了块尺寸与品位、储量、估计精度、选别开采单元的关系,为块尺寸的合理选择提供参考。并以某特大型钼矿为工程背景,进行了深度解析及数据实验,得出了块尺寸不仅影响资源品位分布、矿石量而且影响开采技术经济指标的结论,综合考虑估计精度和选别开采单元,推荐该矿床选择15m×15m×15m的单元块尺寸进行储量估算。     

一种改进的一次范数最小平差方法

一次范数最小平差解的唯一一性，是人们十分关注的问题，而Ｌ－Ｘ－１平差模型未能很好地解决这一问题，为此，本文提出一种改进的一次范数最小平差方法，并对这种改进方法解的精度评定问题作了探讨，最后通过一个算例表明该改进方法非常有效。     

Estimating Climatic Timeseries From Multi-Site Data Afflicted With Dating Error

Timeseries of estimated temperature have been combined to create global or hemispheric climate series over periods exceeding 1000 yr. The data used in these studies, however, may be subject to dating errors. It is shown that when timeseries with dating error are combined, the noise in the data smoothes periodic signals but leaves linear trends intact. This means that the effect of dating error of sample data in a timeseries reconstruction is to smooth out any signals (waves, cycles) that may be present. The purpose of this study was to develop signal extraction methods that will work for this type of historical data. The method used was nonlinear estimation of sample series where dating error has been added by Monte Carlo sampling. Several algorithms were tested for handling the dating error problem. Results were that using nonlinear model fitting, the periods of signals can be identified even from the averaged data. In a second stage of the estimation procedure, the cycle magnitudes can be estimated. Very good fits were achieved for two example cases. Temperature estimation error (white noise due to the use of proxies) was also considered and the method was extended to cover this case with quite good results. Using the new estimation methods, the information inherent in multiple series can be used to overcome the problem of dating error.     

基于丹麦法稳健估计在地铁变形监测中的应用

变形监测在工程项目中是一项非常重要且必不可少的环节,因此,获得原始监测数据并进行有效的处理和预测对项目的安全实施具有关键作用。本文以长春某段地铁监测数据为例,分别用丹麦法稳健估计法和最小二乘法进行数据处理,得出丹麦法稳健估计在单一状态抗拒粗差方面优于最小二乘法的结论。     

Conditional estimation variances: An empirical approach

One of the tasks routinely carried out by geostatisticians is the evaluation of global mining reserves corresponding to a given cutoff grade and size of selective mining units. A long with these recovery figures, the geostatistician generally provides an assessment of the global estimation variance, which represents the precision of the overall average grade estimate, when no cutoff is applied. Such a global estimation variance is of limited interest for evaluating mining projects; what is required is the reliability of the estimate of recovered reserves or, in other words, the conditional estimation variance. Unfortunately, classical linear geostatistical methods fail to provide an easy way to estimate this variance. Through the use of simulated deposits (representing various types of regionalization)the present paper reviews and discusses the effects of changes in cutoff grade and selective mining unit size on the conditional estimation variance. It is shown that, when the cutoff grade is applied to a pointsupport (sample-size)distribution, the conditional estimation variance appears to be readily accessible by classical formulas, once the conditional semivariogram is known. However, the evaluation of the conditional estimation variance seems to be less straightforward for the general case when a cutoff is applied to the average grade distribution of selective mining units. Empirical approximation formulas for the conditional estimation variance are tentatively proposed, and their performance in the case of the simulated deposits is shown. The limitations of these approximations are discussed, and possible ways of formalizing the problem suggested.     

Global estimation variance: Formulas and calculation

This paper discusses the combination of kriging variances, which have been considered heretofor unfeasible since linearity of the problem and considerable simplifications which follow were overlooked. A simplified expression for global estimation variance is presented and an algorithm discussed with respect to precision and computer cost. A case study is presented, and, finally, an optimum calculation method is recommended.     

岩体抗剪强度参数的线性优化方法

针对岩体结构面力学参数的重要性,以大量工程实例为依据,以统计误差分析相关理论为基础,研究最小二乘法与M-估计法在分析结构面抗剪强度参数时的适用性。研究结果表明,在难以判断粗差的数量和比例时,很难对两种线性回归方法的优劣进行规律性的比较。考虑到数据是具有工程特性的,为更准确地处理实验数据,在以上两种方法的基础上提出了一种新的实验数据处理方法,并应用于计算李家河水库的抗剪强度参数。     

回归模型的灵敏度分析

回归计算中，由于资料和计算上的误差，使结果也产生一定的误差，通常，采用最小二乘法或最小一乘法来估计回归模型中的参数，即是取目标函数为最小来实现的，如果使目标函数在允许的误差范围内变化，则参数会有相应的变幅，本文探讨了两变数回归时参数估计的灵敏度，在相关关系不甚密切时，误差对结果的影响是较大的。