系统可靠性增长模型

根据系统在研制期间可靠性的变化规律,考虑维修、改进对系统可靠性的影响,引入改进效果系数,建立了一种基于虚拟工作时间的可修系统可靠性增长模型,可用于完全维修、不完全维修、最小维修和恶化维修.给出了故障强度函数和累积故障次数的表达式,以及模型参数的极大似然估计.算例表明:该模型分析结果与AM-SAA模型一致,且符合工程实际,其参数意义更明确.     

一种基于多跳自相关的差分跳频信号检测方法

针对差分跳频(DFH)信号跳频序列无周期特性和与常规短波跳频信号相似的时频特性给未知参数条件下的检测造成的困难,提出了一种基于多跳自相关的差分跳频信号检测方法.通过深入分析差分跳频信号多跳自相关函数,利用差分跳频信号与噪声信号自相关函数分布特性的不同建立检测统计量,由多跳自相关结果估计跳驻留时间和跳速,用跳驻留时间估计...     

容错控制系统的可靠性建模及模型化简

在容错控制系统的设计过程中,进行系统的可靠性建模和分析求得容错控制系统可靠性是一项非常重要的工作。它是许多设计工作,如设计方案的选择优化和一些设计参数的确定等的重要理论依据。在容错控制系统的可靠性分析中,利用马尔柯夫过程理论对容错控制系统进行可靠性建模能够较为真实地描述系统的实际工作情况,但是由于容错系统为了达到高可靠性而有采用了大量的冗余配置及重构技术,使得该可靠性模型往往变得相当复杂。因此,对     

一种限定虚警概率的PN码捕获自适应门限估计算法

提出了一种限定虚警概率的PN码捕获的自适应门限估计算法,首先在对判决变量的统计特性分析的基础上,计算出了判决门限的有偏估计量;然后分析了估计偏差对捕获系统检测概率和虚警概率的影响;最后,计算机仿真表明,在限定虚警概率的前提下,捕获系统在高斯白噪声信道和瑞利衰落信道下具有较高的检测概率,自适应门限的估计方法易于实现,且适合工程应用。     

基于改进遗传算法的配电网状态估计

利用配电网实时量测数据和规格化的负荷历史数据,以各用户的有功功率和无功功率作为基因,在基因编码和适应度函数中充分考虑用户负荷的概率模型和配电网的潮流约束,采用多种基因操作组合求解,通过IEEE典型算例证明该方法可行,计算精度和速度均满足配电网状态估计的要求.     

雷达波束驻留模式下空间碎片数量的置信区间估计

碎片数量估计是空间碎片环境统计特征描述的重要内容之一,对于空间碎片环境模型验证、航天器碰撞风险分析以及碎片数量增长趋势预测有重要意义.针对波束指向正东、正南任意仰角的雷达波束驻留(Beam-park)模式(天顶指向是波束指向仰角为90°时的特例),给出了一种估计碎片数量置信区间的方法.对于给定轨道高度范围内一个具有穿越雷达波束可能性(即雷达散射截面足够大,且轨道倾角相对测站纬度足够大)的碎片,将其是否真正穿越波束这一随机事件用(0-1)分布来建模,根据所采集的轨道高度和倾角数据,计算出该轨道高度范围内碎片穿越波束的平均概率,进而采用中心极限定理来估计碎片数量的置信区间.仿真结果表明了方法的有效性.      

任意点正弦波信号频率估计的快速算法

研究了任意点正弦波信号频率估计的快速算法,先对截短信号序列(2的整数次幂长度)用M-Rife算法进行频率初估计并得到结果^f,以此作为中心频率,选取^f 21Lfs,-21Lfs两个频率对信号作L点DFT,然后对这两条谱线作频率插值(即Rife算法)得到频率的精确估计。仿真结果表明本算法性能稳定,略优于M-Rife算法,接近克拉美-罗限(CRLB)。该算法便于在DSP,FPGA等器件上实现快速频率估计。     

Efficient and accurate online estimation algorithm for zero-effort-miss and time-to-go based on data driven method

This paper introduces a novel and efficient algorithm for online estimation of zero-effortmiss and time-to-go based on data driven method.Only missile-target separations are utilized to construct the estimation models, and a practical Fisher fusion algorithm is derived to acquire the estimates with high accuracy and computational efficiency.Further, the two parameters can be online estimated at a particular time.Meanwhile, the kinematics equations of the missile-target engagement are independent, and assumptions of the missile guidance system dynamics and behaviors of the missile and target are completely out of consideration.Moreover, the effectiveness and applicability are explicitly verified through various simulation scenarios.     

Non-random vibration analysis for general viscous damping systems

The authors recently developed a kind of non-probabilistic analysis method, named as ‘non-random vibration analysis’, to deal with the important random vibration problems, in which the excitation and response are both given in the form of interval process rather than stochastic process. Since it has some attractive advantages such as easy to understand, convenient to use and small dependence on samples, the non-random vibration analysis method is expected to be an effective supplement of the traditional random vibration theory. In this paper, we further extend the non-random vibration analysis into the general viscous damping system, and formulate a method to calculate the dynamic response bounds of a viscous damping vibration system under uncertain excitations. Firstly, the unit impulse response matrix of the system is obtained by using a complex mode superposition method. Secondly, an analytic formulation of the system dynamic response middle point and radius under uncertain excitations is derived based on the Duhamel's integral, and thus the upper and lower response bounds of the system can be obtained. Finally, two numerical examples are investigated to demonstrate the effectiveness of the proposed method.     

A multi-rate sensor fusion approach using information filters for estimating aero-engine performance degradation

Gas-path performance estimation plays an important role in aero-engine health management, and Kalman Filter(KF) is a well-known technique to estimate performance degradation. In previous studies, it is assumed that different kinds of sensors are with the same sampling rate, and they are used for state estimation by the KF simultaneously. However, it is hard to achieve state estimation using various kinds of sensor measurements at the same sampling rate due to a complex network and physical characteristic differences between sensors, especially in an advanced multisensor architecture. For this purpose, a multi-rate sensor fusion using the information filtering approach is proposed based on the square-root cubature rule, which is called Multi-rate Squareroot Cubature Information Filter(MSCIF) to track engine performance degradation. Soft measurement synchronization of the MSCIF is designed to provide a sensor fusion condition for multiple sampling rates of measurement, and a fault sensor is isolated by maximum likelihood validation before state estimation. The contribution of this paper is to supply a novel multi-rate informationfilter approach for sensor fault tolerant health estimation of an aero-engine in a multi-sensor system. Tests are conducted for aero-engine performance degradation estimation with multiple sampling rates of sensor measurement on both digital simulation and semi-physical experiment.Experimental results illustrate the superiority of the proposed algorithm in terms of degradation estimation accuracy and robustness to sensor failure in a multi-sensor system.