Improved Wavelet-based Spatial Filter of Damage Imaging Method on Composite Structures

Piezoelectric sensor array-based spatial filter technology is a new promising method presented in research area of structural health monitoring (SHM) in the recent years. To apply this method to composite structures and give the actual position of dam-age, this paper proposes a spatial filter-based damage imaging method improved by complex Shannon wavelet transform. The basic principle of spatial filter is analyzed first. Then, this paper proposes a method of using complex Shannon wavelet transform to construct analytic signals of time domain signals of PZT sensors array. The analytic signals are synthesized depending on the principle of the spatial filter to give a damage imaging in the form of angle-time. A method of converting the damage imaging to the form of angle-distance is discussed. Finally, an aircraft composite oil tank is adopted to validate the damage imaging method. The validating results show that this method can recognize angle and distance of damage successfully.     

一种新的航空发动机自适应模型设计与仿真

提出了一种基于机载非线性发动机模型,且具有输入端积分补偿的卡尔曼滤波器估计器的发动机自适应模型设计方法。其主旨是经过相似变换,在非线性相对弱化的另一坐标区域内设计常规卡尔曼滤波估计器,利用所得卡尔曼估计器对各估计回路的初步解耦,进一步在各观测回路中引入输入误差积分激励,对滤波器的输入进行实时积分修正,充分实现各估计参数回路的静态解耦。同时,将该卡尔曼滤波器与机载非线性实时模型综合,从而使发动机自适应模型具有大范围无静差参数跟踪能力。最后,对所提出建立的自适应模型的参数估计能力和鲁棒性进行了数字仿真验证。     

涡轴发动机自适应混合诊断模型高斯加权聚类方法

针对整个飞行包线内涡轴发动机健康参数估计问题,提出基于高斯加权聚类的机载自适应混合模型建立方法.机载自适应混合模型由卡尔曼滤波器和神经网络组成,由于飞行数据样本庞大,采用高斯加权模型对涡轴发动机飞行数据进行实时聚类,利用聚类数据更新神经网络权重,并实现自适应混合模型工作范围的自动扩展.仿真结果表明了该方法的有效性,采用...     

Regularized Robust Filter for Spacecraft Attitude Determination

A modified regularized robust filter is proposed for spacecraft attitude determination in the presence of relative misalignment of attitude sensors. The filter is designed to minimize the worst-possible residual norm on condition that there is parametric uncertainty in the measurement model. The weighting matrix of the residual norm is designed to minimize the upper bound of the estimation error variance. The performance of the proposed attitude determination robust filter is illustrated with the use of real test data from a real three-floated gyroscope. Simulation results demonstrate that the attitude estimation accuracy is improved by using the proposed algorithm.     

多渐消因子Kalman滤波器在SINS初始对准中的应用(英文)

针对系统模型和统计信息不能精确已知的条件下Kalman滤波无法给出最优解这一问题,单一渐消因子Kalman滤波算法对于简单的系统是有效的,但是对于复杂的多变量系统,仅仅利用单个的渐消因子是不够的。本文提出了一种多渐消因子滤波算法,通过利用开窗法计算新息序列协方差的无偏估计获得渐消因子矩阵。利用渐消因子矩阵调节一步预测均方误差矩阵k|k1P,对不同的滤波通道提供不同的渐消速率。将该方法应用于SINS的初始对准中,仿真和试验结果表明:当真实系统噪声统计特性同设定参数不一致时,对准精度明显高于其他滤波算法。其对不确定性噪声具有较低的敏感度,对系统参数具有较好的滤波效果。因而,在实际应用中具有重要的参考价值。     

A Fault-tolerance Estimating Method for Ionosphere Corrections in Satellite Navigation System

 Aiming to the reliable estimates of the ionosphere differential corrections for the satellite navigation system in the presence of the ionosphere anomaly, a fault-tolerance estimating method, which is based on the distributed Kalman filtering, is proposed. The method utilizes the parallel sub-filters for estimating the ionosphere differential corrections. Meanwhile, an infinite norm (IN) method is proposed for the detection of the ionosphere irregularity in the filter processing. Once the anomaly is detected, the sub-filter contaminated by the anomaly measurements will be excluded to ensure the reliability of the estimates. The simulation is conducted to validate the method and the results indicate that the anomaly can be found timely due to the novel fault detection method based on the infinite norm. Because of the parallel sub-filter architecture, the measurements are classified by the spatial distribution so that the ionosphere anomaly can be positioned and excluded more easily. Thus, the method can provide the robust and accurate ionosphere differential corrections.     

数字式重力计量设备电磁兼容性

针对数字式重力计量设备,提出了基于传导电磁干扰(Electromagnetic interference,EMI)噪声抑制的噪声分离网络优化结构和电感电容优化滤波器设计,以及基于辐射噪声抑制的传输线共模电流分析方法,并进行了详细阐述。实验结果表明,本文方法不仅可使设备满足GB9254的EMI检测标准,而且设计的优化滤波器可减小寄生参数影响和降低经济成本,同时辐射噪声抑制避免了借助电波暗室测量及电磁屏蔽等复杂辐射EMI噪声估计和抑制措施。     

性能基导航中对称面内飞行技术误差模型(英文)

飞行技术误差(FTE)与导航系统误差(NSE)是性能基导航(PBN)中总系统误差(TSE)的主要组成部分。性能基导航的实施需要对总系统误差进行航前预测以及航行中的短期动态预测。当飞行技术误差预测值与导航系统误差预测值的和大于PBN导航的规定值时,将无法运行PBN导航。因此,对于总系统误差的两个主要误差分量需要精确建模和透彻分析。采用LQG/LTR方法针对ARIC模型设计了多输入多输出纵向飞行控制系统,分析了在湍流扰动下进近飞行器对称面内的飞行技术误差。基于奇异值理论提出了对称面内飞行技术误差的映射函数以及边界估计模型。模型是基于对对称面内飞行技术误差成型机理的分析提出的,提供了一种基于成型机理的分析和估计方法,从而避免了昂贵试飞和单纯的数据拟合。基于真实数据的仿真验证了对称面内飞行技术误差的理论分析。研究同时揭示了当自动飞行控制系统(AFCS)接通时性能基导航中对称面内飞行技术误差部分由湍流扰动引致,且随湍流强度的增强而增大。     

多传感器加权观测融合自适应UKF滤波器

对于带有相同观测方程和未知噪声统计的非线性多传感器系统,提出了一种基于Sage-Husa估计的自适应UKF滤波算法.该算法利用导出的平稳随机序列的相关函数估计系统观测噪声方差统计R(j),并证明了其收敛性.进而利用Sage-Husa估计算法得到自适应UKF滤波算法.该方法避免了传统Sage和Husa的自适应滤波算法不能处理Q和R均未知的系统的局限性.为了将多传感器信息加以充分利用,提高滤波精度,本文利用加权最小二乘法(WLS),实现了多传感器加权观测融合自适应UKF滤波器.一个带3传感器非线性系统的仿真例子说明了该算法的有效性.     

X射线脉冲星导航中钟差的可观测性问题

标准X射线脉冲星导航(XNAV)能够求解航天器的位置信息,但航天器钟差会导致XNAV的结果产生误差.鉴于脉冲星周期的稳定性,在利用XNAV进行轨道估计中,将钟差作为状态变量进行估计的授时方案已被相关学者提出.一种针对卫星轨道修正专门设计的可观测性分析工具在文中给出,利用其能够有效地判断各个状态的可观测性情况.利用该方法分析将钟差作为状态变量的导航方案,其结果表明仅需2颗脉冲星就可以对全部轨道六根数,以及卫星钟差进行观测;仿真结果验证了可观测性分析结论,双脉冲星导航时系统可以达到60m的定位精度和60ns的授时精度.对比仿真同时揭示了该方案能够有效地抑制钟差对导航精度的影响,将由于钟差引起的定位误差减小20倍以上.理论分析与仿真表明,将钟差作为状态变量的导航方案是一种能够有效地估计钟差,并抑制钟差影响、提升系统估计精度的导航方案.