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.      

A Fast Global Node Selection Algorithm for Bearings-only Target Localization

In the target tracking, the nodes aggregate their observations of the directions of arrival of the target. The network then uses an extended Kalman filter （EKF） to combine the measurements from multiple snapshots to track the target. In order to rapidly select the best subset of nodes to localize the target with the minimum mean square position error and low power consumption, this paper proposes a simple algorithm, which uses the location information of the target and the network. The lower botmd of localization error is utilized according to the distances between the target and the selected active nodes. Furthermore, the direction likelihoods of the active nodes is predicted by way of the node/target bearing distributing relationships.     

基于小波域维纳滤波的激光陀螺数据处理研究

针对激光陀螺随机漂移数据的非平稳特性,设计了小波滤波器,使经小波滤波后的数据近似成为平稳序列,并进行了相应的平稳性检验.在小波变换的基础上,结合维纳滤波器处理平稳信号能力强的特点,提出了一种小波域维纳滤波法.仿真试验表明,此方法更显有效性.     

零差激光干涉仪在超低频大振幅振动测量中的应用

介绍了利用正交的零差激光干涉仪测量安装于振动台面被测靶体的位移,实时计算出运动速度和加速度,从而实现对位移达1m的超低频振动传感器的实时绝对校准。     

固体发动机界面脱粘低温探伤仿真研究

分析了利用工业CT对固体火箭发动机缺陷进行检测的局限性,提出低温冷冻扩大脱粘间隙的方法,利用Ansys软件仿真了同一温度载荷作用下脱粘间隙和初始脱粘长度的关系．得出可以利用低温检测方法部分检测到冷冻前检测不到的脱粘。     

平方根滤波算法在传递对准误差评估中的应用

传递对准误差评估,通常需要进行顺序Kalman滤波及逆序平滑处理。在递推处理过程中,系统状态均方误差阵常常失去非负定性而导致滤波发散。将平方根滤波应用于对准误差的评估中,采用平方根滤波和平方根平滑算法进行弹载子惯导系统的传递对准误差评估,能够保证状态均方误差阵的正定性,并且提高了滤波的收敛速度和评估的误差,为传递对准提供了一种有效的误差评估方法。     

基于抛物线外推的压气机低转速特性研究

针对在建立起动过程数学模型时发动机部件低转速特性难以获取的问题,提出了基于抛物线外推的压气机低转速特性获取方法.给出了两种型号发动机的压气机外推实例,结合发动机部件低转速特性外推的合理性判据可知,所提方法具有较好的准确性和通用性.      

基于迭代容积滤波的无源跟踪算法

对无源目标跟踪问题进行了研究,给出一种只有角度和距离测量的目标跟踪算法。为提高估计的精度和数值稳定性,采用了容积滤波算法,并用基于龙贝格-马尔塔(LM)算法改进迭代容积滤波算法,以提高估计精度,算法实现了对目标的无源跟踪。仿真结果表明:迭代容积滤波算法的跟踪效果更好。     

Autonomous navigation of formation flying spacecrafts in deep space exploration and communication by hybrid navigation utilizing neural network filter

Autonomous navigation of spacecrafts is a difficult task, however, which is a must in future deep space exploration. With multiple spacecrafts flying in space, this aim can be achieved by formation flying spacecraft (FFS) utilizing inverse time difference of arrival (ITDOA) and inverse difference Doppler (IDD) methods, which can locate the position of earth-station from one-way uplink signals in the FFS coordinate, and by way of conversion of coordinates, the position of FFS is achieved in earth-centered earth-fixed (ECEF) coordinate. The ability of neural network (NN) filter in navigation to extract position of spacecrafts from random measuring noise of signal arrival time and Doppler shift is studied with different radius of FFS and surveying parameters. The NN filter used by spacecraft group is new way of unidirectional autonomous navigation and is of high precision of hybrid navigation.     

基于实验的发动机插板式进气畸变压力谐振分析

某型涡扇发动机插板式进气畸变实验中,当插板升高到35%以上,进气截面各个测点畸变扰动出现约为32 Hz大幅振荡.用气流压力波动方程计算了进气道容腔谐振频率为34 Hz.表明该谐振是由插板与发动机之间的容腔引起的.不同转速和流量下,计算和实验的结果都基本稳定.由分析可知:150 Hz以下脉动压力是大幅稳定和周期性的.高频部分主要是小幅随机压力脉动,其速率和加速度变化比较剧烈.在发动机喘振前,谐振频率压力振荡能量大大增加,其它低频和高频成分能量迅速减少,形成典型的谐振型压力振荡.