多边形效应引起同步带直线传动移动误差的分析研究

分析了多边形效应对同步带直线传动移动误差的影响 ,得出误差计算的表达式。通过算例说明同步带及带轮的结构参数对移动误差影响的变化趋势 ,为合理选用同步带传动的结构参数打下基础。

三维动态图像重构特征移动误差消除方法研究

三维动态图像重构过程中,目标物体的特征因发生移动而产生误差,从而降低了三维动态图像重构的精确性。传统的算法不能避免引起目标物体特征移动误差的因素造成的影响。提出采用BP神经网络的三维动态图像重构中的特征移动误差消除方法。利用BP神经网络建立特征移动误差消除模型,对模型中的参数进行训练,利用最速下降学习法可以对模型中各层之间的连接权值进行学习,并反向调节,利用姿态因子对各层的连接权值进行自适应调整,从而使模型的输出误差不断降低,从而降低了特征移动误差。仿真结果表明,利用改进算法能够对三维动态图像重构中的特征移动误差进行消除,提高了三维动态图像重构的精度。

空间多层次误差移动平均模型的广义矩估计——基于广东省产业知识溢出三维非平衡面板数据

构建空间多层次误差移动平均(HSEMA)模型,对HSEMA模型参数采用广义矩估计方法以及可行广义最小二乘法(GMM-FGLS)进行估计。利用HSEMA模型对广东省"时间—地区—产业"三维非平衡面板工业产业数据进行知识溢出实证研究,结果表明,与未考虑层级结构及空间效应的模型相比,HSEMA模型估计结果能更好地反映经济现实,推进了空间多层次误差模型关于空间误差局部相关的研究。当数据存在层级结构和空间特性时,空间多层次误差移动平均模型为经济管理研究提供了一项新的分析工具。

考虑误差移动的区域光伏预测功率修正算法

区域功率预测对电网的安全可靠运行具有重要意义,传统预测方法难以避免云层移动造成的预测误差。提出了一种反馈修正算法,通过误差时间序列的相关性匹配搜索来估计误差的移动,相关系数大小反映了误差移动趋势,根据相关系数设计了不同修正算法;最后,结合某区域实际的光伏出力数据对该方法的有效性进行了验证。研究结果为提高区域功率预测精度提供了一种新的思路。

SLAM问题中机器人定位误差分析与控制

移动机器人同步定位与建图问题(Simultaneous localization and mapping,SLAM)是机器人能否在未知环境中实现完全自主的关键问题之一.其中,机器人定位估计对于保持地图的一致性非常重要.本文分析了SLAM问题中机器人定位误差的收敛特性.分析表明随着机器人的运动,机器人定位误差总体上逐渐增大;在完全未知环境中无法预测机器人定位误差的上限.根据理论分析,本文提出了一种控制机器人定位误差在单位距离上增长速度的算法.该算法通过搜索获得满足定位误差限制的最佳的机器人运动速度,从而控制机器人定位误差的增长.

地面数字移动电视电波传播模型的选择

在分析ITU-R P．370．ITU-R P．1546．ITU-R P．526、Okumura-Hata四种基本传播模型特性的基础上,通过对北京单频网接收场强不同传播模型下的预测,结合北京单频网的实测数据,运用科学的数学检测手段,得出最适合地面数字移动电视在人口稠密、建筑物密集、城市地区网络规划的电波传播模型。

基于马尔科夫链的公交站间行程时间预测算法

公交站间行程时间具有明显的时段分布特征,且公交车辆是典型的时空过程对象,其运行具有状态转移性。为了准确预测公交站间行程时间,在应用马尔科夫链预测公交站间行程时间基础上提出其改进算法。通过大量公交GPS数据构造不同时段下具体线路站间行程时间的马尔科夫状态转移矩阵,并对站间行程时间进行状态推导,采用移动误差补偿法对马尔科夫预测值进行动态修正,改进原有的马尔科夫预测算法。以广州市BRT线路B1的实际运行数据对算法进行了验证,结果表明,移动误差补偿改进算法优于基本马尔科夫算法及BP模型,同时该改进算法还具有实现过程较简单。

构建细节点柱形结构的指纹匹配算法

细节点柱形编码结构是指纹匹配领域中一种新颖的三维数据结构表示。针对这种方法所面临的极大的空间存储代价和时间复杂性,以及对稀疏细节点的描述能力较弱等问题,提出了新的细节点柱形结构的匹配策略,对原有的细节点柱形编码进行改进,减少了柱形编码的计算,有效地降低了匹配时间和空间代价。同时引入了最小形变误差模型,通过对非线性形变进行度量,找回丢失的稀疏细节点对,提高了匹配的准确率。在FVC2004上的实验结果表明,新方法具有较高的效率和准确性。

五分量激光测量装置的试验研究

所讨论的激光测量装置,可以同时测量一个移动轴的5个移动误差分量,即两个直线度分量和3个角位移分量。该装置测量线性误差和角位移误差的精度可分别达到1.5μm和0.5”以内。

外资流入对我国经济影响的统计测算

改革开放以来,流入我国的外资规模不断扩大,这对促进我国国民经济的迅速发展、加快改革步伐起到了积极的作用。本文利用经济统计模型,测算了近10年来外资对我国的GDP、劳动就业、对外贸易、外汇储备和货币流通等几个方面的定量影响,并获得了令人满意的结果。

步进扫描工作台气浮结构分析

着重分析了步进扫描工作台的气浮结构及原理,指出了气浮设计及控制中需要注意的一些问题。

基于动态主元分析法的传感器故障检测

提出了一种基于动态主元分析的传感器故障检测方法。利用数据矩阵前t时刻和当前时刻的数据,建立多变量多时刻的自回归统计模型。计算主元数据矩阵,建立动态主元模型。以测量速度最慢的传感器的测量周期为统一采样周期,4个连续采样周期为一个诊断周期,建立动态三维测量矩阵,采用残差的平方预报误差的指数加权移动平均(Squared prediction error-Exponentially weighted moving average,SPE-EWMA)模型检测传感器故障。在只存在传感器故障的前提下,模拟发动机开车过程中几种典型的渐变性故障和突变性故障,实验结果表明,算法实时跟踪了各种检测指标的变化,准确检测出故障传感器。

双模式神经网络盲均衡算法研究

文中以前馈神经网络作为盲均衡器,根据CMA盲均衡算法及决策指向性算法(DD)提出了两种神经网络学习目标函数,并在对两种目标函数下神经网络盲均衡算法性能分析的基础上,给出了依据移动窗剩余误差理论确定切换门限的方法,提出了双模式神经网络盲均衡算法,并以短数据样本重用确定网络的初始权重.仿真表明文中提出的双模式神经网络盲均衡算法能够克服在单一目标函数下神经网络盲均衡算法的缺陷,且收敛速度快,有效的提高了均衡性能.

Mobile Robot Localization and Navigation System Based on Monocular Vision

A system for mobile robot localization and navigation was presented.With the proposed system,the robot can be located and navigated by a single landmark in a single image.And the navigation mode may be following-track,teaching and playback,or programming.The basic idea is that the system computes the differences between the expected and the recognized position at each time and then controls the robot in a direction to reduce those differences.To minimize the robot sensor equipment,only one omnidirectional camera was used.Experiments in disturbing environments show that the presented algorithm is robust and easy to implement,without camera rectification.The rootmean-square error(RMSE) of localization is 1.4,cm,and the navigation error in teaching and playback is within 10,cm.

Time series prediction of mining subsidence based on a SVM

In order to study dynamic laws of surface movements over coal mines due to mining activities,a dynamic prediction model of surface movements was established,based on the theory of support vector machines(SVM) and times-series analysis.An engineering application was used to verify the correctness of the model.Measurements from observation stations were analyzed and processed to obtain equal-time interval surface movement data and subjected to tests of stationary,zero means and normality.Then the data were used to train the SVM model.A time series model was established to predict mining subsidence by rational choices of embedding dimensions and SVM parameters.MAPE and WIA were used as indicators to evaluate the accuracy of the model and for generalization performance.In the end,the model was used to predict future surface movements.Data from observation stations in Huaibei coal mining area were used as an example.The results show that the maximum absolute error of subsidence is 9 mm,the maximum relative error 1.5%,the maximum absolute error of displacement 7 mm and the maximum relative error 1.8%.The accuracy and reliability of the model meet the requirements of on-site engineering.The results of the study provide a new approach to investigate the dynamics of surface movements.

Novel multipath routing protocol integrated with forward error correction in MANET

In order to improve the data transmission reliability of mobile ad hoc network, a routing scheme called integrated forward error correction multipath routing protocol was proposed, which integrates the techniques of packet fragmenting and forward error correction encoding into multipath routing. The scheme works as follows: adding a certain redundancy into the original packets; fragmenting the resulting packets into exclusive blocks of the same size; encoding with the forward error correction technique, and then sending them to the destination node. When the receiving end receives a certain amount of information blocks, the original information will be recovered even with partial loss. The performance of the scheme was evaluated using OPNET modeler. The experimental results show that with the method the average transmission delay is decreased by 20% and the transmission reliability is increased by 30%.

MPLPK:A mobile path localization protocol based on key nodes

To alleviate the localization error introduced by irregular sensor network deployment, a new mo bile path localization based on key nodes （MPLPK） protocol is proposed. It can recognize all con cave/convex nodes in the network as fixed anchor nodes, and simplify the following localization process based on these key nodes. The MPLPK protocol is composed of three steps. After all key nodes are found in the network, a mobile node applying improved minimum spanning tree （MST） algorithm is introduced to traverse and locate them. By taking the concave/convex nodes as anchors, the complexity of the irregular network can be degraded. And the simulation results demonstrate that MPEPK has 20% to 40% accuracy improvements than connectivity-based and anchor-free three-di- mensional localization （CATL） and approximate convex decomposition based localization （ACDL）.

A Precise Localization Method for a High Speed Mobile Robot Using iGS and Dual Compass

This paper proposes a precise localization algorithm for a quickly moving mobile robot.In order to localize a mobile robot with active beacon sensors,a relatively long time is needed,since the distance to the beacon is measured by transmitting time of the ultrasonic signal.The measurement time does not cause a high error rate when the mobile robot moves slowly.However,with an increase of the mobile robot’s speed,the localization error becomes too high to use for accurate mobile robot navigation.Therefore,in this research into high speed mobile robot operations,instead of using two active beacons for localization,an active beacon and dual compass are utilized to localize the mobile robot.This new approach resolves the high localization error caused by the speed of the mobile robot.The performance of the precise localization algorithm is verified by comparing it to the conventional method through real-world experiments.