Power network parameter estimation method based on data mining technology

The parameter values which actually change with the circumstances, weather and load level etc.produce great effect to the result of state estimation. A new parameter estimation method based on data mining technology was proposed. The clustering method was used to classify the historical data in supervisory control and data acquisition (SCADA) database as several types. The data processing technology was impliedto treat the isolated point, missing data and yawp data in samples for classified groups. The measurement data which belong to each classification were introduced to the linear regression equation in order to gain the regression coefficient and actual parameters by the least square method. A practical system demonstrates the high correctness, reliability and strong practicability of the proposed method.     

基于层次分析法的区间估计的车站能力查定误差因子分析研究

本文归纳总结了车站能力查定计算过程中存在的多种影响因素,深入分析了其产生原因和不可避免性。然后利用层次分析法的区间估计方法计算得出各种误差因子对计算结果的影响权重大小,并对比不同误差因子的权重区间,筛选出强误差因子,剔除弱误差因子,为精确计算车站能力值提供依据。     

液压驱动转盘在海洋固定平台模块钻机上的设计与应用

海洋固定平台模块钻机空间狭小、布局紧凑、要求设备具有尺寸小、质轻、集成度高、运行安全可靠等特点,而传统电机驱动转盘的驱动方式存在传动链长、传动部件多、传动装置复杂、结构尺寸庞大等问题,在模块钻机尺寸有特殊要求的情况下安装难度大、使用和维修不便,影响总体布局和结构形式的设计。针对上述情况,通过液压驱动转盘与电驱动转盘进行对比,总结出液压驱动转盘小巧轻便、易于建造安装、能够优化钻台结构、操作维护费用低、安全可靠等特点,可为空间有特殊要求的海洋固定平台模块钻机提供一定的参考。     

基于频域搜索的梳状谱信号检测方法

由于梳状谱信号多普勒容限较小,利用常规的匹配/相关检测方法进行检测时,需要较大数量的拷贝信号与计算量。针对这一问题,本文提出一种基于频域搜索的梳状谱信号检测算法。通过利用梳状谱信号频域多峰结构的特点,根据信号的先验信息计算出不同径向速度下回波信号的频点分布,对接收的信号在频域进行搜索累计的方法同时实现信号的检测与速度估计。仿真分析证明了本文算法的有效性。     

基于EMD的矢量水声器方位估计算法

对经验模态分解算法(EMD算法)进行深入研究,对其基本原理、基本性质以及存在的问题进行分析。为改善EMD算法在方位估计的精度,减少高频噪声、间断干扰的影响,本文采用Hilbert-Huang变换方法来消除模态混叠现象。实验结果表明,本文提出的基于EMD的矢量水声器方位估计算法,能够有效提高方位估计的精度。     

基于Simulink及ASAM标准的可变维数查表功能研究与实现

基于Simulink及ASAM标准,研究了可变维数查表功能的嵌入式实现与操作方法,并在INCA环境下,对可变维数查表功能进行了测试,测试结果表明,可变维数查表功能能够满足不同的MAP维数应用需求,可以使ECU控制系统软件具有更好的可扩展性、可维护性以及通用性。     

Application of frequency estimation algorithm based on a single vector sensor in underwater acoustic communication

1 Introduction1 An acoustic vector sensor (AVS) simultaneously measures the acoustic pressure and the components of acoustic particle velocity which render the basis for developing new signal processing methods[1-2]. The higher processing gain can be obta…     

Min-norm spatial spectrum based on acoustic vector-sensor linear array

1 Introduction1 The Min-Norm(MN) algorithm was proposed by Kumaresan and Tufts[1] for estimating the DOA of targets applied at pressure sensor arrays. It has been proved that lower bias and higher resolution of DOA estimation using the MN algorithm is obt…     

基于三电平逆变器的永磁同步电动机直接转矩控制新方法

在永磁同步电动机数学模型和三电平空间矢量调制法的基础上,提出一种基于三电平逆变器拓扑结构的永磁同步电机直接转矩控制新方法.该方法采用bang-bang控制器对电机进行控制,通过新型合成矢量开关表对固定合成矢量的选取,有效地抑制了三电平逆变器直流侧支撑电容中点电位波动、限制了输出电压变化率dv/dt并降低了开关损耗,同时...     

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.