采用仿射不变矩的谐振接地系统故障选线方法研究

对谐振接地系统单相接地故障特征的分析表明,单相接地初始阶段故障线路与健全线路间的零序电流波形相似度低于各健全线路间的零序电流波形相似度,且故障初始时刻故障线路与健全线路的零序电流极性相反,高阻接地时该结论仍成立。仿射不变矩恰能反映各零序电流波形的整体形状特征和极性关系,且不受波形平移、旋转和缩放等仿射变换的影响,抗干扰能力强。对从各故障暂态零序电流波形图中提取的仿射不变矩特征量进行谱系聚类分析,并计算聚类有效性指标,选取聚类有效性最高的聚类树实现故障选线。各种故障工况的大量仿真表明,该选线方法适应性好,可靠性高。     

Identification of task model using piecewise affine systems with variable switching points and its application

This paper considers a human‐operated task model based on identification techniques using switched systems expressed by mixed logical dynamical systems. In the system, each subsystem is expressed by a piecewise affine system. For a model to be identified, it is not easy to determine a number of subsystems in advance. In this paper, we propose a simultaneous identification technique which takes into account both a number of subsystems and parameters, so that a piecewise affine model of a human operation can be obtained. In addition, the obtained model is applied to automation. The effectiveness of the proposed method is illustrated by simulations and experiments. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 176(1): 46–54, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21079     

A projection method for the numerical solution of linear systems in separable stiff differential equations

This paper deals with the efficient implementation of implicit methods for solving stiff ODEs, in the case of Jacobians with separable sets of eigenvalues. For solving the linear systems required we propose a method which is particularly suitable when the large eigenvalues of the Jacobian matrix are few and well separated from the small ones. It is based on a combination of an initial iterative procedure, which reduces the components of the vector error along to the nondominant directions of J and a projection Krylov method which reduces the components of the vector error along to the directions corresponding to the large eigenvalues. The technique solves accurately and cheaply the linear systems in the Newton's method, and computes the number of stiff eigenvalues of J when this information is not explicitly available. Numerical results are given as well as comparisons with the LSODE code.     

Sequential slippage tests using Robbins-Lai's invariant confidence sequences

The paper deals with two kinds of location-slippage testing problems.The alternative hypothesis says that there is a single slippage in one kind of problems,and that there are multiple slippages in the other kind. In a location slippage model, by using Robbins' inequality, Robbins-Lai's invariant confidence sequences for slippage are constructed for both of the problems and sequential slippage tests using those confidence sequences are proposed.     

关于量子Poincaré-Cartan积分不变量

基于相空间Ｇｒｅｅｎ函数的生成泛函，导出了普遍情况下正规Ｌａｇｒａｎｇｅ量系统和奇异 Ｌａｇｒａｎｇｅ量系统的量子Ｐｏｉｎｃａｒé－Ｃａｒｔａｎ（ＰＣ）积分不变量．证明了该不变量与量子正则方程等价．当变换的Ｊａｃｏｂｉ行列式不为１时，仍可导出量子ＰＣ积分不变量；这与量子Ｎｏｅｔｈｅｒ定理不同．并将量子ＰＣ积分不变量与经典情况作了对比．结果表明：经典和量子ＰＣ积分不变量成立的条件和表达式均不同．     

An approach to dark energy problem through linear invariants

The time evolution of vacuum energy density is investigated in the coherent states of inflationary universe using a linear invariant approach. The linear invariants we derived are represented in terms of annihilation operators. On account of the fact that     

一种改进的SIFT双向匹配算法

分析SIFT特征提取匹配算法，利用SIFT特征向量匹配对的唯一性约束改进算法的匹配策略提出双向匹配算法，在已有匹配结果的基础上引入匹配的唯一性约束，进一步降低实时图像与参考图像时序匹配的误匹配率，以达到在实时图像中寻找已知着陆区域的目的，提高图像匹配的准确率。实验结果表明该方法有效。     

Invariant 2D object recognition using KRA and GRA

Computer vision has been extensively adopted in industry for the last two decades. It enhances productivity and quality management, and is flexibility, efficient, fast, inexpensive, reliable and robust. This study presents a new translation, rotation and scaling-free object recognition method for 2D objects. The proposed method comprises two parts: KRA feature extractor and GRA classifier. The KRA feature extractor employs K-curvature, re-sampling, and autocorrelation transformation to extract unique features of objects, and then gray relational analysis (GRA) classifies the extracted invariant features. The boundary of the digital object was first represented as the form of the K-curvature over a given region of support, and was then re-sampled and transformed with autocorrelation function. After that, the extracted features own the unique property that is invariant to translation, rotation and scaling. To verify and validate the proposed method, 50 synthetic and 50 real objects were digitized as standard patterns, and 10 extra images of each object (test images) which were taken at different positions, orientations and scales, were acquired and compared with the standard patterns. The experimental results reveal that the proposed method with either GRA or MD methods is effective and reliable for part recognition.