基于神经网络的开环光纤陀螺误差补偿方法

根据开环光纤陀螺线性度课差随角速度增大而增大的特性,提出了在大角速度情况下应用神经网络对陀螺误差进行建模并补偿,在小角速度时对陀螺输出数据进行平滑滤波以抑制噪声的分段误差补偿方法.在速率转台上对开环光纤陀螺(VG941)进行测试并采集了测量范围内陀螺的多组实际输出数据,基于这些数据对单输入单输出的神经网络进行训练,得到了开环光纤陀螺的神经网络模型.在所得模型基础上,对整个测量范围内的陀螺原始输出数据采用分段补偿方法进行了陀螺误差补偿,并使开环光纤陀螺最大线性度误差由15%下降到0.3%,提高了开环光纤陀螺的测量精度.实验结果表明基于神经网络的开环光纤陀螺误差补偿方法对提高开环光纤陀螺的精度、扩大其应用范围具有实用价值.     

光纤陀螺随机漂移辨识方法研究

陀螺随机漂移是影响惯性导航和组合导航精度的重要因素.为了有效辨识出光纤陀螺随机漂移噪声的参数,采用了自相关函数、功率谱密度和Allan方差对实测陀螺数据进行分析.实验结果表明:自相关函数、功率谱密度和Allan方差都能有效辨识出陀螺输出信号中的角度随机游走噪声,只有Allan方差能辨识出其中的角速率随机游走噪声.功率谱...     

光纤陀螺误差的实时建模与补偿

通过对干涉型光纤陀螺误差来源及其影响因素的分析,建立了与温度变化量及温度变化速率相关的角速率误差概率密度函数,并提出一种针对慢时变与弱非线性随机过程的分段等概率误差补偿方法.该方法采用非线性手段,对一系列具有统计平稳性的随机过程进行参数估计与预测,能够实现模型动态跟踪,近似程度较高,且充分发挥了并行计算的优势,可避免由补偿过程所造成的输出时间滞后.几种典型工作状况下的实际补偿结果表明其能有效地减小角速率及航向角误差.     

光纤陀螺捷联系统振动误差补偿研究

针对舰船振动环境对光纤陀螺捷联系统性能的影响,提出基于神经网络的非线性数学补偿方案。对加速度计信息作傅里叶分析,进行振动特征提取;利用提取的振动特征值作为输入向量进行BP神经网络训练,建立光纤陀螺误差输出模型;对陀螺进行在线补偿,减小振动引起的漂移误差,提高了捷联系统初始对准精度。     

基于LS-SVM的开环光纤陀螺误差补偿方法

针对开环光纤陀螺标度因数是非线性的,而且随着输入角速度增大,光纤陀螺线性度误差也越大的问题,提出采用基于最小二乘支持向量机(LS-SVM)的分段误差补偿方法.以LS-SVM和直接近似法补偿误差大小为依据,确定分段门限值.采用实测转台上先纤陀螺VG941在全量程范围内的输入输出数据为训练和检验样本.结果表明分段误差补偿方法使光纤陀螺最大线性度误差由15%降至2‰,验证了方法的可行性和有效性,提高了开环光纤陀螺的精度.     

光纤陀螺随机漂移测试与建模

文中介绍了光纤陀螺(FOG)随机漂移的测试方法和实验设备,探讨了一种利用AIC准则和长自回归法建立随机漂移ARMA模型的新途径.利用实验平台对光纤陀螺输出信号进行了采集,对原始数据进行了平稳化处理,然后进行了光纤陀螺随机漂移ARMA建模实验,并通过白噪声检验验证了用新方法建立的ARMA模型具有很好的适用性.     

光子晶体光纤及其在光纤陀螺中的应用

光子晶体光纤是一种包层由空气孔-石英沿轴向方向周期排列所构成的新型光纤。光子晶体光纤特殊的结构分布和特性,使其在降低光学噪声、陀螺尺寸、温度敏感性,提高陀螺精度和抗核辐射等方面,具有传统光纤陀螺不可比拟的优越性。本文综述了光子晶体光纤的概念、在光纤陀螺方面的独特优势,以及其在光纤陀螺应用方面的研究进展和前景。     

光纤陀螺的研究进展及其应用现状

综合论述了各种类型的光纤陀螺的工作原理及其发展状况，报道了光纤陀螺实用化进展．展示了光纤陀螺在未来惯导技术中的重要地位．     

浅谈光纤陀螺技术及其工程应用

介绍了光纤陀螺技术的原理、分类、性能参数,概述了该技术的国内外研究现状及发展方向、应用领域,重点探讨了在大坝变形监测中的应用原理、技术要求和可行性分析。     

应用随机游走的社交网络用户分类方法

针对现有在线社交网络用户分类方法不能有效利用用户属性和关系网络信息提高分类性能的问题,设计了一种基于随机游走模型的多标签分类方法MLCMRW。该方法的分类过程包括学习用户初始化类别标签以及通过迭代推理获得用户稳定标签分布两个阶段,并且其可以同时考虑用户属性以及关系网络特征信息进行分类。多个在线社交网络数据集上进行的实验表明,MLCMRW比其它已有的代表性方法有更好的分类性能,并且更适合对现实中的在线社交网络进行用户分类。     

基于互相关的二阶段时间序列聚类方法

提出了一种高效的时间序列聚类方法,以互相关函数为基础,通过二阶段的方法实现更低时间复杂度下的时间序列聚类。第一步以时间序列符号化为基础,通过设计符号化序列特征抽取算法,抽取特征时间段;第二步以互相关函数为基础,通过改进的互相关函数步骤,实现更快速的时间序列聚类。实验结果表明,该方法可以适应稀疏及密集的时间序列数据抽取,同时与传统的聚类距离公式相比,处理速度更快,对时间序列形状的缩放有更好的表示效果,并能保持较高准确性。     

基于互相关的有效奇异值消噪方法

为了提高信号的信噪比,针对奇异值分解消噪方法中用于重构的有效奇异值个数难以确定问题,提出了一种基于互相关的有效奇异值选取方法,进而达到消噪的目的。该方法利用单个奇异值重构得到的分量信号,求互相关,从而确定用于重构的有效奇异值个数。通过采用含有不同频率成分的带噪信号对该方法进行验证,并与同类奇异值选择方法进行对比,结果表明,该方法不仅简单易行而且效果较好。     

Color image segmentation in HSI space for automotive applications

This article presents a method for classifying color points for automotive applications in the Hue Saturation Intensity (HSI) Space based on the distances between their projections onto the SI plane. Firstly the HSI Space is analyzed in detail. Secondly the projection of image points from a typical automotive scene onto the SI plane is shown. The minimal classes relevant for driver assistance applications are derived. The requirements for the classification of the points into those classes are obtained. Several weighting functions are proposed and a fast form of an euclidean metric is investigated in detail. In order to improve the sensitivity of the weighting function, dynamic coefficients are introduced. It is shown how to compute them automatically in order to get optimal results for the classification. Finally some results of applying the metric to the sample images are shown and the conclusions are drawn.

A novel continuum robotic cable aimed at applications in space

We introduce a new class of long and thin continuum robots intended for use in space applications. This ‘cable’ robot is a next-generation version of the current state of the art (NASA’s ‘Tendril’). The article describes the key practical limitations of the mechanical design of ‘Tendril’. We introduce the design specifics of our novel concept for a next-generation device with significantly enhanced performance. Equipped with a light and compact motor-encoder actuation mechanism, the new design has improved compliance and possesses a concentric backbone arrangement which is tendon-actuated and spring-loaded. A new forward kinematic model is developed extending the established models for constant-curvature continuum robots, to account for the new design feature of controllable compression (in the hardware). The model is validated by performing experiments with a three-section prototype of the design. The new model is found to be effective as a baseline to predict the performance of such long and thin continuum ‘cable’ robots.     

基于空间模型及连通域分析的异纤维在线检测

针对一直困扰棉纺企业的异性纤维问题,从工程实际出发,提出一种快速高效的棉花异纤维在线检测及定位方法。该方法在RGB颜色空间建立了一种判断异性纤维的检测模型及模型参数的离线学习方法,以实现棉花与异性纤维的快速分割;基于形态学处理及连通区域分析算法实现异纤维的准确定位。进一步通过对剔除系统中电磁阀的响应特性测试,提出了剔除时间补偿的思想,可以保证对异性纤维的精准剔除。实验结果表明,该方法能够有效地检测并剔除棉花中的大部分异性纤维。     

Fuzzy PID control of space manipulator for both ground alignment and space applications

Considering gravity change from ground alignment to space applications, a fuzzy proportional-integral-differential (PID) control strategy is proposed to make the space manipulator track the desired trajectories in different gravity environments. The fuzzy PID controller is developed by combining the fuzzy approach with the PID control method, and the parameters of the PID controller can be adjusted on line based on the ability of the fuzzy controller. Simulations using the dynamic model of the space manipulator have shown the effectiveness of the algorithm in the trajectory tracking problem. Compared with the results of conventional PID control, the control performance of the fuzzy PID is more effective for manipulator trajectory control.     

Wandering crowd simulation based on space syntax theory

Space syntax has proven there appears to be a fundamental process that informs human and social usage of an environment,and the effects of spatial configuration on movement patterns are consistent with a model of individual decision behavior.Introducing space syntax to crowd simulation will enable space structure guide the random movement of the crowd with no specific targets.This paper proposes a simulation method of the wandering crowd,which calculates the crowd distribution corresponding to the space through space syntax and uses a hybrid path planning algorithm to dynamically navigate the crowd to conform to the distribution.Experiments show the presented method can obtain reasonable and vision-realistic simulation results.     

基于EPF最大互相关配准的机械臂目标识别方法

针对工业机械臂在复杂背景下多目标并存识别问题,提出一种基于边缘势场函数最大互相关匹配算法。该算法引入边缘势场函数(edge potential function,EPF)理论计算目标图边缘点的势场函数,有效地利用了复杂结构中单边缘点的联合效用,并在特征点变换模型约束下采用最大互相关相似性度量完成同名控制点的建立与目标配准定位。仿真实验表明,该算法对因成像条件引起噪声旋转的复杂背景图像识别效果良好,精准度高于传统相关匹配算法。     

基于k近邻的批次过程在线实时监测方法

针对基于k近邻的故障检测方法(Fault Detection method using the k-Nearest Neighbor rule,FD-kNN)的在线实时监测需预估当前时刻之后的采样数据,检测性能会受到预估精度影响的问题,对FD-kNN进行扩展以适用于批次过程的实时监测.该方法根据每个采样时刻的历史数据进行建模,并根据这些模型实时监测批次过程.该方法不需要预估数据,避免由于预估误差大而带来的误报和漏报问题,同时较好地继承k近邻法则(k-Nearest Neighbor rule,kNN)在处理非线性、多模态和非高斯等问题上具有的优势.青霉素发酵过程的仿真试验验证该方法可行.     

Online correction MPC strategy for spatially-distributed system based on PCA method

In this paper, the online correction model predictive control (MPC) strategy is presented for partial dif- ferential equation (PDE) unknown spatially-distributed systems (SDSs). The low-dimensional MIMO models are obtained using principal component analysis (PCA) method from the high-dimensional spatio-temporal data. Though the linear low- dimensional model is easy for control design, it is a linear approximation for nonlinear SDSs. Thus, the MPC strategy is proposed based on the online correction low-dimensional models, where the state at a previous time is used to correct the output of low-dimensional models and the spatial output is correct by the average deviation of the historical data. The simulations demonstrated show the accuracy and efficiency of the proposed methodologies.