基于卡尔曼滤波器及神经网络的发动机故障诊断

提出了一种基于卡尔曼滤波器及神经网络的航空燃气涡轮发动机气路故障诊断的方法.该方法用卡尔曼滤波器来估计发动机可测参数的变化量,再由神经网络来映射发动机性能参数的变化量,并据此进行发动机气路故障诊断.数字仿真表明,该方法是可行的,有效的.      

多传感器组合导航系统的改进多尺度滤波算法

多尺度滤波算法在多传感器组合导航系统中已得到成功应用，然而该算法用到多个时刻的量测向量，导致算法计算量过大，并影响系统的实时性。针对上述问题，首先利用分块技术与小波变换将时域内描述的系统原始状态方程转换为块状态方程，然后将实时得到的当前时刻的量测向量表达为块状态向量的形式，最后结合常规卡尔曼滤波技术与序贯滤波的思想，提出了一种改进的多传感器组合导航系统多尺度滤波方法。将该算法应用于GPS/SST/SINS多传感器组合导航系统，仿真结果验证了该算法不仅具有较好的实时性，而且相对于传统算法,系统的定位精度提高1倍以上。     

State estimate for stochastic systems with dual unknown interference inputs

Stochastic system state estimation subject to the unknown interference input widely exists in many fields, such as the control, communication, signal processing, and fault diagnosis. However, the research results are mostly limited to the stochastic system in which only the dynamic state model or the measurement model concerns the individual unknown interference input, and the state model and the measurement model are both with the same unknown interference input. State estimate of the stochastic systems where the state model and the measurement model contain dual Unknown Interference inputs (dual-UI) with different physical meanings and mathematical definitions is concerned here. Firstly, the decoupling condition with the Unknown Interference input in the State model (S-UI) is shown, which introduces the decoupled system with the adjacent Measurement concerned Unknown Interference inputs (M-UI) appearing in the state model and the measurement model. Then, through defining the Differential term of the adjacent M-UI (M-UID), the equivalent system with only M-UID in the state model is obtained. Finally, considering the design freedom of the equivalent system, the decoupling filter in the minimum mean square error sense and the adaptive minimum upper filter with different applicable conditions are represented to obtain the optimal and sub-optimal state estimate, respectively. Two simulation cases verify the effectiveness and superiority compared with the traditional methods.     

Guidepost-based autonomous orbit determination method for GEO satellite

Guidepost-based navigation system is a novel autonomous orbit determination method for the GEO satellite. The system is achieved by using the camera imaging function to obtain the guidepost images and the GNSS signal receiver to obtain the pseudoranges between the GEO and the navigation satellites. Due to the high altitude of GEO satellite and the time-varying sunlight condition in the space environment, it may be difficult to obtain object image points and the distance measurements of GNSS because of the weak visibility of the guideposts. To deal with the problem, a novel integrated orbit determination system is presented. The Earth landmarks, the in-orbit spacecraft and GNSS navigation satellites whose line-of-sights and the distance can be easily obtained are used at the same time as information for the GEO satellite navigation based on the observability conditions analysis. The observability of the GEO satellite navigation system is analyzed through the physical observability, the mathematical observability and the engineering observability through the observing geometry, the rank of observability matrix and the Cramer-Rao lower bound (CRLB) respectively. Besides, the maximum correntropy unscented Kalman filter (MCUKF) algorithm is applied to improve the estimation stability of the system in the presence of non-Gaussian noises. The simulation indicates the feasibility of the proposed scheme.     

采用单目视觉的非合作目标星状态估计

针对微小卫星逼近观测未知的空间翻滚非合作目标星任务，提出一种基于单目视觉的目标星相对状态估计方法。在建立追踪星/目标星相对运动模型的基础上，以单目相机识别并测量获得的目标星固有特征的像素位置为观测输入，通过扩展卡尔曼滤波算法实现对目标星相对位置、相对速度、相对姿态、角速度、惯量比和特征位置等状态的估计。仿真结果表明,该方法能够很好地实现对未知非合作目标星的相对状态估计，姿态估计误差小于2°，位置估计误差小于0.1 m，特征点位置平均估计误差小于0.04 m。     

用于平台连续瞄准和校准的卡尔曼滤波器

本文为提高制导精度,讨论了用于惯性平台的连续瞄准、校准的卡尔曼滤波器,介绍平台系统和加速度表的误差模型、参数辨识的卡尔曼滤波方法及重力残数加速度表校准原理。     

基于模拟退火算法预测储层参数

讨论了如何将地震资料、测井信息和先验地质知识有机地结合起来预测储层参数，以便揭示储层内部细节和纵横向变化特征。通过将模拟退火算法与人工神经网络相结合，能够解决非线性全局优化问题，勾画出地震信息和储层参数之间的复杂关系，为储层特征描述和储层横向预测提供提供直观、可靠的地层参数剖面一孔隙度、砂泥质百分含量、含水饱和度及渗透率等剖面。     

带限信号采样和数字相参处理

传统的相参处理器包括Ｉ，Ｑ二个通道，存在不避免的幅相不平衡，本文研究中频带限信号采样经数字处理获得零中频正交数字信号的方法，该方法只用一路Ａ／Ｄ转换器直接对中频带限信号进行采样和数字变换，用镜频抑制滤波器，二次重采样移频电路分离零中频信号的同相分量Ｉ。和正交分量Ｑ，因而，该方法能够克服Ｉ，Ｑ通道不平衡，文中对中频频率，采样时钟周期的选择，镜频抑制滤波器的设计进行了详细讨论，选用具有线性相位特性的Ｆ     

用高速数字信号处理器实现雷达视频杂波模拟

研究了雷达视频杂波的实时模拟方法。雷达杂波通常为随机过程。假定杂波包络服从莱斯分布，其功率谱为立方型，这种杂波可用伪随机序列通过特定的滤波器产生。杂波滤波器组可用ＴＭＳ３２０Ｃ２５数字信号处理器完成，并与缓冲存储器相组合，实现Ｉ，Ｑ两路杂波数据实时输出。ＴＭＳ３２０Ｃ２５数字信号处理器运算速度高、指令功能强，有利于提高杂波模拟速度和模拟器的可编程性。实验中选用双极点递归滤波器产生立方谱杂波数据。计     

基于时间序列数据挖掘的旋转机械故障预报

提出一种基于时间序列数据挖掘的故障预报新方法。把故障前兆因子作为一种暂态,根据旋转机械轴承振动的实验数据建立时间序列．利用时延嵌入的方法重构状态空间,在状态空间中使用遗传算法搜寻最优暂态束．组成暂态集。用暂态集对旋转机械轴承振动的测试数据进行分析．判断是否为故障前兆因子．从而实现故障预报。