自适应抗差UKF算法在GPS/BD-2组合系统中的应用

针对非线性系统中因噪声模型不准确或测量数据中存在野值而导致无迹卡尔曼滤波（UKF）结果产生偏差甚至发散的问题,提出了一种自适应抗差无迹卡尔曼滤波（ARUKF）算法。该算法利用抗差估计原理构造抗差方差分量统计量,并由该统计量引入自适应因子来调节增益矩阵,减弱野值对滤波的影响。将ARUKF 算法应用于GPS/BD-2组合导航系统中,仿真实验结果表明,当观测数据中存在野值时,ARUKF算法能够有效地控制观测异常误差的影响,定位精度得到了很大提高,并在不同系统噪声和观测噪声方差下,具有较好的鲁棒性和实时性。     

F_2型离子膜电解槽室框密封泄漏点的消除方法

消除F2型离子膜电解槽阴阳极室框密封泄漏点是电解槽检修中的主要内容。介绍了几种消除密封泄漏点的方法,该方法简捷、实用、安全,既保证了生产的正常进行,又减少了检修工作量,并指出了消除泄漏点的几种应该纠正的错误检修方法。     

硫酸污水除氟处理研究

提出了硫酸污水除氟的"电石渣中和-混凝"工艺.探讨了不同的絮凝剂及其用量、反应液pH、反应时间及条件等因素对除氟效率的影响,提出了最佳工艺条件.     

基于图像二值化处理的混纺图像杂色去除方法的研究

混纺织物图像中由于摄取设备及其周围环境的影响使图像中存在了很多杂色。为了去除图像中无效的杂色提取有效的色彩,必须对原始图像进行杂色处理。提出一种基于图像二值化处理的杂色去除方法,通过将混纺图像二值化,与原混纺图像进行像素点运算处理,能有效去除混纺杂色。实验结果表明这种方法具有简单、准确和快速等特点。     

图像特征匹配中一种高效的鲁棒估计算法

在图像特征匹配过程中,误匹配不可避免。提出一种新的基于拓扑约束（顺序约束和仿射不变约束）的外点去除算法,用于快速地去除图像粗匹配结果中的误配点。该算法 对随机采样集进行拓扑过滤,只对满足拓扑约束的采样集进行计算。实验表明,该算法相比于传统的鲁棒估计算法RANSAC和改进的PROSAC算法,大大提高了计算效率并保持很高的 计算精度,有助于提升图像匹配性能及3维重建的精度和鲁棒性。     

CLT型静电旋风除尘器性能的实验研究

研究了用 CLT 型旋风子制作的静电旋风除尘器的性能,即在不同入口风速及不同电场电压下除尘效率与阻力。得出了静电旋风除尘器的除尘效率,在一定风速范围内及特定电压下的“峰值”规律.     

Enhancing minimum spanning tree-based clustering by removing density-based outliers

Traditional minimum spanning tree-based clustering algorithms only make use of information about edges contained in the tree to partition a data set. As a result, with limited information about the structure underlying a data set, these algorithms are vulnerable to outliers. To address this issue, this paper presents a simple while efficient MST-inspired clustering algorithm. It works by finding a local density factor for each data point during the construction of an MST and discarding outliers, i.e., those whose local density factor is larger than a threshold, to increase the separation between clusters. This algorithm is easy to implement, requiring an implementation of iDistance as the only k-nearest neighbor search structure. Experiments performed on both small low-dimensional data sets and large high-dimensional data sets demonstrate the efficacy of our method.     

A bootstrap test for additive outliers in non‐stationary time series

In this paper we propose a new procedure for detecting additive outliers in a univariate time series based on a bootstrap implementation of the test of Perron and Rodríguez (2003, Journal of Time Series Analysis 24, 193‐220). This procedure is used to test the null hypothesis that a time series is uncontaminated by additive outliers against the alternative that one or more additive outliers are present. We demonstrate that the existing tests of, inter alia, Vogelsang (1999, Journal of Time Series Analysis 20, 237–52) Perron and Rodríguez (2003) and Burridge and Taylor (2006, Journal of Time Series Analysis 27, 685–701) are unable to strike a balance between size and power when the order of integration of a time series is unknown and the time series is driven by innovations drawn from an unknown distribution. We show that the proposed bootstrap testing procedure is able to control size to such an extent that its size properties are comparable with the robust test of Burridge and Taylor (2006) when the distribution of the innovations is not assumed known, whilst maintaining power in the Gaussian environment close to that of the test of Perron and Rodríguez (2003).     

Robust inversion method for jointly estimating parameters and variance components from heterogeneous monitoring data

In this paper, a novel inversion method is proposed for jointly robust estimation of parameters and variance components from disjunctive groups of observations affected by outliers. This method, named robust non-negative variance component estimation (RVCE), is a coupling of variance component estimation (VCE) technique with a robust estimation method, developed to cope with outliers and to avoid negative variance, leading thus, to an estimation reliable enough. The principle of RVCE method is based on the refinement of the stochastic model via an equivalent weight matrix established from the original measurement weight matrix and an adapted full weight matrix with hard rejection to outliers. This last one is derived from the robust standardized residuals, using a highly robust estimator, as an initial solution of the inverse problem, and a cut-off value adapted to sort out the good observations from the bad ones. Furthermore, because the original weight matrix is partly known, the integration of the VCE technique plays a key role to reach an optimal solution and to provide valuable information on the precision of the estimates. The performance of the proposed method is demonstrated by considering a rockfill dam as an example, where the material parameters and variance components are jointly estimated from geotechnical and geodetic measurements. The results of comparison study between RVCE method with other methods such as the classical NN-VCE, RIMCO, least squares and the combined Huber’s M-estimator with VCE (HVCE) for various configuration options have highlighted the pertinence of the proposed method.     

Distribution-Free Life Test Sampling Plans

This paper describes life test sampling plans which assume only that the life distribution has increasing or decreasing failure rate. Tables are presented showing the minimum number of items necessary to assure a specified mean life or percentile life when the experiment time is fixed in advance.