航电系统SCI互连的可靠性模型研究

研究未来航电系统关键协议——SCI(可扩展的一致性接口)的可靠性建模问题.从SCI互连的基本模型出发,提出了基于任务的系统可靠性分析方法,建立了系统的可靠性模型,并针对航电系统中SCI的蝶型互连进行了可靠性分析,指明该方法在航电系统设计阶段对于任务划分和拓扑选择都将起到指导作用.      

BP神经网络用于传感器故障诊断的仿真研究

在标准逆传播神经网络的基础上 ,提出了一种全新的改进逆传播神经网络 ,用来消除标准逆传播神经网络收敛速度慢和易陷入局部最小点的缺陷 ;并且设计了一个主神经网络和三个分布神经网络的结构 ,通过神经网络的在线学习 ,得到需要的参数估计。用它与传感器测得的实际值比较 ,可判断出故障 ,并且给出了仿真实例。     

降维法计算扩展网络的最短路径

以在军事等领域具有重要应用的扩展网络为研究对象,研究并提出了基于最短路树的网络降维方法。当子网络之间有边互连的节点数远小于原网络节点数时,利用降维网络计算扩展网络的最短路径具有很好的效果。     

航空发动机神经网络内模控制

基于神经网络内模控制理论研究了神经网络内模控制方法在航空发动机控制系统中的应用,建立了基于Elman网络的航空发动机多变量内模控制系统。采用Elman网络建立发动机内模型和内模控制器,详细介绍了建模、控制的算法及其实现过程。取部分飞行条件下的数据作为学习样本,采用动态BP算法对神经网络权值进行调整,并在飞行包线内其它工作点对整个控制系统进行了仿真。结果表明,使用神经网络建立的航空发动机内模控制系统具有良好的控制品质和较强的自适应能力。      

基于Kohonen自组织网络算法规划数控抛光路径

为避免在数控抛光中因采用规则运动路径产生的规律性高频误差,故借助于神经网络方法,采用基于Kohonen自组织网络算法,对抛光头的运动路径进行规划。     

基于BP神经网络的零件成组技术的研究

提出了一种基于BP神经网络的零件分类方法。通过200个典型零件样本对神经网络进行训练和测试,证明该基于BP神经网络的零件分类成组系统可实现零件的准确分类成组。     

基于QoS的卫星网络端-端通信可靠性分析

针对卫星网络动态环境下的高速信息传输、业务类型差异大等特点，提出一种综合考虑各业务QoS（Quality of Service）指标的可靠性分析方法。在卫星通信网络实际运行周期内，通信系统往往处于逐渐劣化过程中，导致卫星的节点和链路除正常工作和完全失效外，还存在部分失效的工作状态。本文在链路多状态基础上基于最小路集算法（Minimum Path Set Algorithms，MPSA）在不同业务的QoS指标（时延、带宽和丢包率）约束下，得出满足该业务QoS约束的所有可靠路径集，对路径集中路径进行不交化处理得到网络端-端可靠性。研究结果表明，不同业务由于QoS需求的差异导致网络端-端可靠性不同，所提算法与传统算法相比更加符合实际。由于实际卫星网络环境中会采用端-端并行多路径传输（Multi-Path Transmission，MTP），本文在上述研究的基础上，进一步对多路径的端-端可靠性进行了研究，结果表明多路径数据传输可靠性高。     

FLOLS误差源建模与仿真研究

菲涅尔光学助降系统(FLOLS)是典型的舰载机光学着舰引导系统。分析了影响FLOLS着舰引导精度的指示误差源和光学误差源,包括稳定平台跟踪误差、光源位置与理想着舰点位置偏差、光源温度、飞行员视觉误差,研究了FLOLS相关系统的工作原理和着舰引导误差的产生机理,建立了各误差源的数学模型。通过对FLOLS着舰过程进行重复仿真,使用标准偏差统计方法,得到各着舰引导误差的统计特性,进而得出各误差源影响着舰精度程度比较。     

Advanced multiple response surface method of sensitivity analysis for turbine blisk reliability with multi-physics coupling

To reasonably implement the reliability analysis and describe the significance of influencing parameters for the multi-failure modes of turbine blisk, advanced multiple response surface method(AMRSM) was proposed for multi-failure mode sensitivity analysis for reliability. The mathematical model of AMRSM was established and the basic principle of multi-failure mode sensitivity analysis for reliability with AMRSM was given. The important parameters of turbine blisk failures are obtained by the multi-failure mode sensitivity analysis of turbine blisk. Through the reliability sensitivity analyses of multiple failure modes(deformation, stress and strain) with the proposed method considering fluid–thermal–solid interaction, it is shown that the comprehensive reliability of turbine blisk is 0.9931 when the allowable deformation, stress and strain are3.7*10~(-3)m, 1.0023*10~9 Pa and 1.05*10~(-2)m/m, respectively; the main impact factors of turbine blisk failure are gas velocity, gas temperature and rotational speed. As demonstrated in the comparison of methods(Monte Carlo(MC) method, traditional response surface method(RSM), multiple response surface method(MRSM) and AMRSM), the proposed AMRSM improves computational efficiency with acceptable computational accuracy. The efforts of this study provide the AMRSM with high precision and efficiency for multi-failure mode reliability analysis, and offer a useful insight for the reliability optimization design of multi-failure mode structure.     

Dynamics of air transport networks: A review from a complex systems perspective

Air transport systems are highly dynamic at temporal scales from minutes to years. This dynamic behavior not only characterizes the evolution of the system but also affect the system's functioning. Understanding the evolutionary mechanisms is thus fundamental in order to better design optimal air transport networks that benefits companies, passengers and the environment. In this review, we briefly present and discuss the state-of-the-art on time-evolving air transport net-works. We distinguish the structural analysis of sequences of network snapshots, ideal for long-term network evolution (e.g. annual evolution), and temporal paths, preferred for short-term dynamics (e.g. hourly evolution). We emphasize that most previous research focused on the first modeling approach (i.e. long-term) whereas only a few studies look at high-resolution temporal paths. We conclude the review highlighting that much research remains to be done, both to apply already available methods and to develop new measures for temporal paths on air transport networks. In particular, we identify that the study of delays, network resilience and optimization of resources (aircraft and crew) are critical topics.