A Failure Sample Selection Method Based on Failure Pervasion Intensity

The complex and uncertain relationship among failures was always ignored in failure sample selection based on traditional testability demonstration experimental method. A failure pervasion model is founded based on fuzzy probability Petri net （FPPN） which can depict the propagation and pervasion relation among failures, then failure pervasion intensity is defined, the process of failure pervasion was depicted based on k-step fault pervasion algorithm and the pervasion inten- sity was expressed by a value. The method of sample selection based on failure pervasion intensity and failure rate is intro- duced into the process of sample selection. The practical application shows that the sample set selected based on failure pervasion intensity and failure rate can represent the failure set adequately.     

Study on System Failure Probability Model Based on Dynamic Fault Tree

Aiming at the characteristics of complex logic relation and multiple dynamic gates in system, its failure probabil- ity model is established based on dynamic fault tree. For the multi-state dynamic fault tree, it can be transferred into Markov chain with continuous parameters. The state transfer diagram can be decomposed into several state transfer chains, and the failure probability models can be derived according to the lengths of the chains. Then, the failure probability of the dynamic fault tree analysis （DFTA） can be obtained by adding each chain＇ s probability. The failure probability calculation of DFTA based on the continuous parameter Markov chain is proposed and proved. Given an example, the analytic method is compared with the conventional methods which have to solve the differential equation. It is known from the results that the analytic method can be applied to engineering easily.     

Computer Vision Method in Human Motion Detection

Human motion detection based on computer vision is a frontier research topic and is causing an increasing attention in the field of computer vision research. The wavelet transform is used to sharpen the ambiguous edges in human motion image. The shadow＇s effect to the image processing is also removed. The edge extraction can be successfully realized. This is an effective method for the research of human motion analysis system.     

Study on Guidance Law of UAV Net Recovery System

The design and realization of a net recovery system is introduced, which can recover UAV （unmanned aerial vehicle） reliably and safely. The mathematical model is built, and the horizontal and vertical guidance law is studied based on the aerodynamic parameters and actual flying trial data of a certain UAV. The simulation result shows that this system can realize the recovery safely, stably and accurately.     

Research on Instantaneous Thrust Measurement for Attitude-control Solid Rocket Motor

In order to measure the instantaneous thrust of a certain attitude-control solid rocket motor, based on the analysis of the measurement principles, the difference between the instantaneous thrust and steady thrust measurements is pointed out. According to the measurement characteristics, a dynamic digital filter compensation method is presented. Combined the identification-modeling, dynamic compensation and simulation, the system＇s dynamic mathematic model is established. And then, a compensation digital filter is also designed. Thus, the dynamic response of the system is improved and the instantaneous thrust measurement can be implemented. The measurement results for the rocket motor show that the digital filter compensation is effective in the instantaneous thrust measurement.     

Fault Diagnosis of Bearing Based on Integration of Nonlinear Geometric Invariables

A fault diagnosis method of bearing based on integration of non-linear geometric invariables was presented for the non-linearity exiting in bearing system but ignored in traditional fault diagnosis.The meanings of non-linear geometric invariables,such as fractal dimension,Lyapunov exponent,Kolmogorov entropy,correlation distance entropy and their calculation method were analyzed.Grey theory is applied to integrate these parameters and the correlation values as fault characteristic value was input into the support vector machines for diagnosis.The experimental results show that this method can distinguish the bearing fault effectively,it provides a new approach for the fault diagnosis of rotating machinery.     

Conversion of Torpedo＇s Lake and Sea Test Data Based on Grey System Theory

As only a little information can be obtained from torpedo＇s lake and sea tests, and the torpedo＇s life does not distribute typically. If conventional methods are used to convert the environment factor for torpedo＇s lake and sea tests, their results can not reflect the actual conditions. A conversion model of the environment factor for torpedo＇s lake and sea tests is set up based on the GM（1,2） model of the grey system theory. For the merit of the grey system, the problem of uncertain life distributions and few samples can be solved. The calculation results show that the method is easy, realistic and high precise.     

Numerical Simulation of Airflow Field and Structure Improvement in Engine Compartment of Armored Vehicles with Electric Transmission

When the mechanical drive is changed into the electric transmission,the cooling system of the engine compartment should be altered to meet the new requirement for the increasing in equipment such as electric apparatus.In order to predict and analyze the rationality of cooling system in the virtual engine compartment,the numerical simulation of airflow fields in the engine compartment by using computational fluid dynamics（CFD） technique is necessary.An armored vehicle with electric transmission in the research is taken as the research object.The physical model and mathematical model for the computation of 3D air flow and heat transfer in the engine compartment of an armored vehicle with electric transmission is established.Turbulent flow in the compartment is described by using the standard k-ε two-equation turbulence model.The temperature and velocity fields of 3D air flow in the engine compartment are numerically simulated and analyzed based on different fan＇s flux.A theoretical basis for determination of the fan＇s flux is given by the simulation results.The positions of the air-vent shutter are analyzed.The simulation results show that the different positions of the air-vent shutter can lead to different cooling efficiencies.     

Numerical Simulation for Ventilated Supercavitation High Speed Underwater Vehicle

Supercavitation is a revolutionary technique to achieve high drag reduction for underwater vehicle. It can help us to break through the conventional speed barrier. This article presents a numerical algorithm for ventilated supercavitation flow field based on mixture multiphase flow model, briefs the calculation results and compares them with that tested in high-speed water tunnel and towing tank. The mathematical model, its numerical calculation method, computational region and boundary conditions are discussed in detail. Some pertinent nondimensional parameters about the ventilated supercavitation, such as geometrical configuration of supercavity, drag coefficient and ventilation rate are investigated. Reynolds number is selected to predict gas ventilation rate instead of Froude number. Finally, based on the test and simulation results, a semi-empirical formula of the ventilation rate estimation suitable for different conical angle caritators is proposed.     

基于广义随机Petri网的导弹系统测试性建模与指标评估方法研究

针对目前导弹测试性指标论证时缺乏有效方法支撑的问题,提出了一种基于广义随机Petri网（GSPN）的测试性建模方法。在建立导弹系统三维立体结构GSPN模型基础上,以各子系统的平面GSPN模型为研究对象,分析导弹系统故障检测及维修过程,同时根据国家军用标准GJB/Z1391—2006 故障模式影响及危害性分析指南对系统故障模式进行分类;基于GSPN模型可达标识图与嵌入马尔可夫链同构,以实存状态集和消失状态集表征库所变迁,采用同构法对测试性指标进行求解;以某型导弹子系统为例,对其测试性指标进行了评估,得到92%的故障检测率和90%的故障隔离率,验证了所提建模方法和相应算法的有效性,对测试性指标的权衡分析与评估具有指导意义。     

复杂可修系统任务测试性建模

为了更加合理地衡量复杂可修系统执行任务过程中的测试性,建立一种符合复杂可修系统功能特性和任务特点的物理模型和数学模型。分析了复杂可修系统任务测试性参数,选取任务故障检测率和任务故障隔离率作为度量参数,结合系统测试性功能层次结构,建立系统任务测试性物理模型,并在此基础上,建立系统串并混联的任务测试性数学模型,针对某型潜艇燃油分系统开展验证分析工作。分析结果表明：该模型贴近实际,适用于复杂可修系统任务测试性建模。     

一种基于多信号流图的雷达系统测试性建模分析方法

为了在产品的设计早期获得检测率、隔离率等测试性数据,提出一种应用多信号流图模型方法进行系统测试性建模与分析的方法。基于雷达等电子产品结构复杂、解析建模困难的特点,分析了雷达系统的功能结构、工作模式及FMEA结果,并以某雷达系统为例建立系统的多信号流图,利用TEAMS软件提供的工具,对系统的测试性水平进行了分析和评估。实例分析结果表明:改进的雷达系统的测试性设计能够满足指标要求,多信号流图建模分析方法对于测试性分析和评估行之有效。     

基于广义随机有色Petri网的测试性建模方法

针对现有测试性模型简化系统故障与测试之间的关系,忽略故障模式之间复杂性的问题,提出一种基于广义随机有色Petri网（CGSPN）的测试性建模方法。在Petri网的理论基础上对故障模式复杂性进行分析,并用不同颜色表示严酷度等级,完成CGSPN模型的构建。应用编码方案区分同一故障的多种故障模式,有效降低建模难度。采用可达性算法获取相关性矩阵。引入三角模糊数算法获取专家知识,将专家数据作为先验信息与后验测试数据相结合,解决数据量少和不可靠问题。以某型导弹为例建立CGSPN模型,对其进行测试性分析,得到96.8%的故障检测率和100%的故障隔离率,在满足系统测试性指标要求基础上丰富了模型的内容,为装备的测试性建模提出了一种新方法。     

基于层次Bayesian网络及后验风险准则的故障样本量确定方法

针对现有测试性验证方法对装备系统结构考虑不足,且在双方风险约束条件下所确定的故障样本量过大问题,提出一种基于层次Bayesian网络和后验风险准则的故障样本量确定方法。根据装备系统结构建立测试性验证方法的层次Bayesian网络模型,并以故障检测率作为Bayesian网络 的传递参数;提出Bayesian网络不确定性推理算法,充分融合各层次测试性先验信息,同时基于偏度-峰度检验的拟合分布选取方法推导出系统故障检测率联合先验分布;进一步结合系统成败型数据确定其后验分布,基于后验样本数据集和Bayes后验风险准则设计故障样本量确定算法,通过实例进行分析。结果表明,与经典验证方法、传统Bayesian方法相比,所提方法在相同双方指标约束下能有效降低样本量。     

基于层次广义随机Petri网的测试性建模新方法

针对目前装备系统采用层次化、模块化设计,维修级别与测试性建模复杂度大大提高的问题,提出一种基于层次广义随机Petri网（HGSPN）的测试性建模方法。将主流模型和广义随机Petri网（GSPN）模型进行对比,阐明主流模型存在的问题,以及选择GSPN模型的原因;对装备进行层次划分,建立分层GSPN模型;系统及其组成元件存在多个故障模式,为区分这些故障模式提出一套完整编码方案;给出可达性算法获取层次相关性矩阵,运用测试性评估数学模型得到各层级的测试性水平,将各层级的测试性信息汇总,得到装备完整的测试性水平。以某型导弹发动机系统为例,建立其HGSPN模型,并对测试性指标进行确定,得到100%的故障检测率和66.7%的故障隔离率,验证了所提建模方法和相应算法的有效性。     

基于广义随机Petri网的鱼雷系统级测试性参数确定方法

在装备论证阶段,提出科学合理的测试性指标要求,可以有效指导测试性设计。目前鱼雷武器系统还缺乏有效的测试性参数定量分析方法,在综合比较现有各种测试性需求分析模型的基础上,提出了一种基于广义随机Petri网的测试性建模方法。通过构建鱼雷武器系统基层级维修保障流程的广义随机Petri网模型,得到状态可达图,并利用同构法,求解了测试性参数与可用度之间的关系;以可用度和平均故障修复时间为设计指标,对国外某型鱼雷的测试性参数进行了求解,并利用Petri网 建模工具PIPE4.3.0软件进行了仿真分析,验证了模型和算法的有效性。     

基于故障扩散强度的故障样本选取方法

传统的测试性验证试验样本选取方法没有考虑测试对象的各故障模式之间的复杂性与不确定性关系。针对这一问题，建立了一种基于模糊概率Petri网的复杂系统故障扩散模型，该模型完备地描述了测试对象故障模式之间的传播扩散关系，并引入故障扩散强度概念，按分步扩散的原则对故障扩散过程进行描述，给出了每个故障的扩散强度量值。提出了基于故障率和故障扩散强度的故障样本选择方法，案例验证结果表明，基于该方法选择的故障样本集更能覆盖测试对象的故障模式集。     

某战术导弹舵机系统BIT分析

针对日益复杂的武器系统故障检测难题,设计了某战术导弹舵机系统BIT。本文首先对舵机系统BIT进行了分析,然后介绍了其设计原理,并提出了减少BIT虚警的措施,最后进行了可测试性预计。该预计结果表明,舵机系统BIT故障检测率符合设计要求。     

多故障诊断策略优化生成技术研究

故障诊断策略设计是测试性设计的重要内容。已有的测试性分析与诊断工具通常做了单故障假设，不适用于复杂系统。针对这一问题，提出了多故障隔离策略优化生成算法。该方法首先采用布尔逻辑运算生成每步测试执行后的完备最小割集，然后采用基于信息量启发式算法生成近似最优的多故障隔离策略。最后应用案例进行了验证，结果表明：本文提出的算法可以有效地生成多故障诊断策略。由于测试与故障的定义是广义的，因此该算法可用于系统级、部件级以及元件级的多故障诊断策略的优化生成。