基于研制信息的测试性验证试验方案研究

针对现有测试性验证试验方案需要较大故障样本量的问题,提出了一种利用研制信息制定测试性验证试验方案的新方法。首先,在二项分布经典抽样模型的基础上,运用证据理论方法,研究了基于测试性试验数据、测试性预计结果和专家经验等研制信息的基本信任分配函数的构造方法,建立了基于融合不同种类研制信息的测试性验证试验方案,并确定了该方案的存在性,给出了方案的确定方法,最后开展了案例应用研究。由于充分考虑了研制信息,因此在确保有较好的验证效果的条件下,与传统的试验方案相比,该方法可以明显减少故障样本量,或在样本量保持不变的情况下有效降低双方风险。     

面向测试性虚拟验证的功能-故障-行为-测试-环境一体化模型

 由于测试性预计和测试性试验验证客观存在的困难及问题,测试性虚拟验证将在测试性工程领域发挥重要作用.根据测试性虚拟验证对模型的需求,针对传统测试性模型存在的定量特征少、导致测试性评估结果不准确等问题,提出一种功能-故障-行为-测试-环境一体化模型.首先,分析并指出该一体化模型由功能、故障、行为、测试、环境5大类要素构成.然后,在数学上对该一体化模型及其子模型进行定义和描述,分析并建立各子模型之间的关联关系.最后以某导弹及其测试系统为案例进行实验和应用研究.结果表明,在建模信息量充足的情况下,基于该一体化模型得到的测试性虚拟试验验证与评估结果较准确,能较好地支持装备测试性摸底、鉴定与验收等.     

基于仿真数据的测试性验证序贯设计方案

针对当前测试性验证试验设计方案均存在确定的故障样本量较大以及验证周期长的问题,提出了一种基于仿真数据的测试性验证序贯设计方案。首先,基于二项分布模型确定序贯设计的判决阈值;然后,在序贯试验下基于给定的样本量分配和故障模式选取方法,采用仿真的方式生成相应的故障模式并进行验证试验。同时,以序贯方式计算相应的概率比,通过其取值动态判定接受/拒收。结果表明,与传统方法相比,该方法与经典验证方法具备几乎相同的抽样特性,能达到有效减少测试性验证试验所需故障样本量的目的。     

小子样复杂装备系统测试性评估中的验前参数值确定方法

针对当前小子样测试性评估中对验前信息处理不规范、结果可信度差的问题,研究了由专家经验信息、子系统试验信息和虚拟仿真信息确定系统测试性验前参数值的方法.根据不同来源的测试性验前信息,分别提出了模糊不确定性加权、分系统数据折合和基于相似度量的Dempster-Shafer(D-S)证据融合方法估计系统测试性验前参数值.实例分析表明:该方法计算测试性评估中的验前参数值比其他文献方法的计算结果低约0.8%.     

机载系统测试性设计体系研究

军用飞机在外场表现出诊断能力不足的现象,严重影响飞机再次出动的效率。从军用飞机故障诊断 的实际使用需求出发,深入分析机载系统在设计、试验过程中存在的测试性设计问题;针对军用飞机整个研制 与使用过程,明确设计目标,提供设计、验证和评估方法,将原来相互孤立的设计工作进行整合,提出一套完整 的机载系统测试性设计体系,并对测试性设计过程中的诊断能力设计、测试性试验等关键环节进行深入剖析; 同时,在工作方法、专业定位和制度保障方面提出改进建议,能够有效促进测试性设计有机地融入机载系统的 设计过程,提升机载系统测试性水平,提高飞机综合诊断能力。     

基于优化SPOT和D-S证据理论的测试性验证方案

针对现有基于序贯验后加权检验的测试性验证方案对测试性设计指标之间的模糊参数空间考虑不足，以及未能充分运用测试性多源先验信息的问题，提出一种优化序贯验后加权检验和D-S证据理论相结合的测试性验证方案。首先，考虑测试性设计指标之间的模糊参数空间，构建三参数空间复杂假设，并基于Bayes理论研究序贯决策规则，同时确定决策因子以及决策阈值；其次，以测试性指标构成的参数空间为辨识框架，分别构造基于专家信息以及测试性试验数据等先验信息的基本信任分配函数，建立融合多源先验信息的优化序贯验证方案；最后，结合实例进行研究，并与经典验证方案、传统Bayes验证方案、序贯概率比检验方案以及序贯验后加权检验方案进行了对比分析。结果表明，该方案由于考虑了模糊参数空间以及充分融合了多源先验信息，有效解决了模糊参数空间的处理问题，同时所确定的平均故障样本量在决策支持的参数空间均优于其他方法。     

测试性验证中抽样方案的精确算法及应用

通过对二项分布函数单调性的讨论,提出了求解二项分布函数联立不等式的精确算法,可迅速准确地获得测试性验证的抽样方案。并研制了测试性验证软件包,可以较好地满足测试性验证的要求。     

Testability integrated evaluation method based on testability virtual test data

Testability virtual test is a new test method for testability verification, which has the advantages such as low cost, few restrictions and large sample of test data. It can be used to make up the deficiency of testability physical test. In order to take the advantage of testability virtual test data effectively and to improve the accuracy of testability evaluation, a testability integrated eval- uation method is proposed in this paper based on testability virtual test data. Considering the char- acteristic of testability virtual test data, the credibility analysis method for testability virtual test data is studied firstly. Then the integrated calculation method is proposed fusing the testability vir- tual and physical test data. Finally, certain helicopter heading and attitude system is presented to demonstrate the proposed method. The results show that the testability integrated evaluation method is feasible and effective.     

基于通用充分性准则的测试性试验方案研究

建立了故障模式与被测单元(UUT)特性之间的关系模型,根据关系模型建立了样本集的通用充分性准则。在通用充分性准则的基础上,研究了确定试验方案的新方法,包括确定样本量和建立样本集的方法,以及相应的合格判断方法。通过实例应用说明了方法的可行性。与现有方法相比,新方法更适用于现有的指标要求情况和多参数综合试验的需求,而且建立的样本集可以覆盖UUT的重要特性。     

一种基于ROM模型的测试性指标论证方法

针对实践中缺乏理论性、可实施性强的测试性指标论证方法的现状,提出了一种基于可靠度、战备完好率与可维修度（ROM）模型的测试性指标论证方法。从战备完好率（O）、可靠度（R）、可维修度（M）关系式入手,将关系式中的可靠度和可维修度分别用平均故障间隔时间（MTBF）和平均修复时间（MTTR）替换,再建立MTBF和MTTR与故障诊断率、虚警率和机内测试（BIT）故障率的关系式并代入"ROM"关系式,得到战备完好率与测试性指标之间的关系式,建立待解指标与BIT数量之间的关系式,通过代入和消减参数得到战备完好率随BIT数量变化曲线,通过找到曲线极值点得到最佳BIT数量,进而得到最佳的测试性指标。在模型构建和指标求解过程中进行了较为充分的仿真分析,得到了大量与经验相符的规律性结论,为不同对象应用该方法进行参数设置时提供了较为充分的参考。最后应用本文方法对某光电一体化设备进行了指标论证,演示并验证了本文方法的有效性。     

Testability evaluation using prior information of multiple sources

Testability plays an important role in improving the readiness and decreasing the lifecycle cost of equipment. Testability demonstration and evaluation is of significance in measuring such testability indexes as fault detection rate（FDR） and fault isolation rate（FIR）, which is useful to the producer in mastering the testability level and improving the testability design, and helpful to the consumer in making purchase decisions. Aiming at the problems with a small sample of testability demonstration test data（TDTD） such as low evaluation confidence and inaccurate result, a testability evaluation method is proposed based on the prior information of multiple sources and Bayes theory. Firstly, the types of prior information are analyzed. The maximum entropy method is applied to the prior information with the mean and interval estimate forms on the testability index to obtain the parameters of prior probability density function（PDF）, and the empirical Bayesian method is used to get the parameters for the prior information with a success-fail form. Then, a parametrical data consistency check method is used to check the compatibility between all the sources of prior information and TDTD. For the prior information to pass the check, the prior credibility is calculated. A mixed prior distribution is formed based on the prior PDFs and the corresponding credibility. The Bayesian posterior distribution model is acquired with the mixed prior distribution and TDTD, based on which the point and interval estimates are calculated.Finally, examples of a flying control system are used to verify the proposed method. The results show that the proposed method is feasible and effective.     

一种基于二次分配的测试性指标分配方法

针对现有主流测试性分配方法均为一次性分配，缺乏必要的反馈和修正，一旦有单元分配指标过高无法实现，会导致系统指标也无法实现的问题，提出了一种基于二次分配的测试性指标分配方法。利用基于反正切函数的改进故障率分配法实施初次分配，由单元开展测试性初步设计和预计，基于单元测试性指标预计结果判断是否需要实施再次分配，如需要再次分配，则基于单元相对难度系数的修正函数，对指标偏高/偏低的单元实施再次分配，得到最终分配结果。通过仿真算例和实例验证了二次分配方法的有效性和先进性。     

故障诊断策略的优化方法

 以相关性模型为基础,综合可靠性和测试费用等因素提出了一种系统级优选测试点方法和故障诊断策略。首先根据系统的相关性矩阵,将测试性度量、故障概率和测试费用统一考虑,推导出测试点的故障诊断信息量计算公式;然后根据信息量的大小依次选择测试点,并确定出优化的故障诊断策略。所得到的故障诊断策略确保了在较低的测试费用下,使用尽可能少的测试步骤快速完成系统的故障检测和隔离。     

Sensor Optimization Selection Model Based on Testability Constraint

Sensor selection and optimization is one of the important parts in design for testability. To address the problems that the traditional sensor optimization selection model does not take the requirements of prognostics and health management especially fault prognostics for testability into account and does not consider the impacts of sensor actual attributes on fault detectability, a novel sensor optimization selection model is proposed. Firstly, a universal architecture for sensor selection and optimization is provided. Secondly, a new testability index named fault predictable rate is defined to describe fault prognostics requirements for testability. Thirdly, a sensor selection and optimization model for prognostics and health management is constructed, which takes sensor cost as objective function and the defined testability indexes as constraint conditions. Due to NP-hard property of the model, a generic algorithm is designed to obtain the optimal solution. At last, a case study is presented to demonstrate the sensor selection approach for a stable tracking servo platform. The application results and comparison analysis show the proposed model and algorithm are effective and feasible. This approach can be used to select sensors for prognostics and health management of any system.     

导弹装备测试性数据相关性分析研究

针对目前装备使用阶段测试性数据来源于专家信息这类存在不确定性因素的信息,会直接影响测试性验证结论的准确性和完整性。为了增加测试性数据的可信度,基于导弹装备使用阶段测试性数据,提出了灰色关联分析的方法流程,对数据进行相关性分析。结果表明,基于灰色关联算法的数据相关性分析方法能得到测试性数据可信度程度,并挖掘出测试性指标间潜在的关联规律,能丰富专家信息,有助于提高验证准确度。     

考虑测试性设计缺陷修正延时的测试性增长模型建模与评价方法

针对现有测试性增长模型忽略了测试性设计缺陷的修正延时过程，进而导致测试性增长模型（TGM）跟踪与预计精度低的问题，提出了一种考虑测试性设计缺陷修正延时的测试性增长模型建模理论与方法。首先分析测试性设计缺陷识别与修正之间的延时机理，得到剩余测试性设计缺陷（TDL）具有先增后减的铃形变化趋势；在此基础上，分别以Gamma、Raleigh和Delay-S 3种曲线拟合剩余测试性设计缺陷（RTDL）变化趋势，研究建立基于以上3种曲线考虑修正延时的测试性增长模型；最后，以某机载稳定跟踪平台测试性增长试验数据验证测试性增长模型拟合、跟踪及预计效能。研究结果表明：基于该测试性增长试验数据，Gamma曲线可以精确地拟合剩余测试性设计缺陷变化规律，测试性增长模型跟踪和预计精度可达到10^-2数量级。     

测试性研制阶段数据评估验证方法

分析了现有测试性验证方法应用情况,阐述了测试性研制阶段数据评估验证方法的必要性。通过与现有测试性验证方法的对比分析,提出了一种新的测试性验证方法,并说明了该验证方法的含义和特点。该验证方法可用于故障检测率、故障隔离率和虚警率的验证。建立了该验证方法的工作框架,包括验证要求、验证程序、验证技术和验证组织。重点阐述了该验证方法的两种工作方式实施流程、适用的最小样本量范围、测试性数据收集表格和测试性数据判据。其中,测试性数据收集表格可以记录故障检测、故障隔离和虚警信息。进行了案例应用,给出了数据分析结果和经验总结。案例应用表明该方法能够达到测试性验证的效果。     

A novel approach of testability modeling and analysis for PHM systems based on failure evolution mechanism

Prognostics and health management (PHM) significantly improves system availability and reliability, and reduces the cost of system operations. Design for testability (DFT) developed concurrently with system design is an important way to improve PHM capability. Testability modeling and analysis are the foundation of DFT. This paper proposes a novel approach of testability modeling and analysis based on failure evolution mechanisms. At the component level, the fault progression-related information of each unit under test (UUT) in a system is obtained by means of failure modes, evolution mechanisms, effects and criticality analysis (FMEMECA), and then the failure-symptom dependency can be generated. At the system level, the dynamic attributes of UUTs are assigned by using the bond graph methodology, and then the symptom-test dependency can be obtained by means of the functional flow method. Based on the failure-symptom and symptom-test dependencies, testability analysis for PHM systems can be realized. A shunt motor is used to verify the application of the approach proposed in this paper. Experimental results show that this approach is able to be applied to testability modeling and analysis for PHM systems very well, and the analysis results can provide a guide for engineers to design for testability in order to improve PHM performance.     

基于序贯回归的小样本测试性验证试验方案

针对现有测试性验证试验方案难以实现较小样本量下满足置信水平要求的测试性评估问题,提出了基于序贯回归的小样本测试性验证试验方案。提出并证明了成败型试验序贯样本回归可行性假设;对序贯样本进行回归分析,实现了小样本下的测试性评估;建立了评估优化方案,实现了满足置信水平要求的测试性评估。实例验证表明:该方法可同时适用于有双方风险要求和置信水平要求的场合,且完所需样本量明显减少,在案例中平均减少了22.3%,最大减少了85%。      

A novel testability model for health management of heading attitude system

Prognostics and health management (PHM) is very important to guarantee the reliability and safety of aerospace systems, and sensing and test are the precondition of PHM. Integrating design for testability into early design stage of system early design stage is deemed as a fundamental way to improve PHM performance, and testability model is the base of testability analysis and design. This paper discusses a hierarchical model-based approach to testability modeling and analysis for heading attitude system health management. Quantified directed graph, of which the nodes represent components and tests and the directed edges represent fault propagation paths, is used to describe fault-test dependency, and quantitative testability information is assigned to nodes and directed edges. The fault dependencies between nodes can be obtained by functional fault analysis methodology that captures the physical architecture and material flows such as energy, heat, data, and so on. By incorporating physics of failure models into component, the dynamic process of a failing or degrading component can be projected onto system behavior, i.e., system symptoms. Then, the analysis of extended failure modes, mechanisms and effects is utilized to construct fault evolution-test dependency. Using this integrated model, the designers and system analysts can assess the test suite’s fault detectability, fault isolability and fault predictability. And heading attitude system application results show that the proposed model can support testability analysis and design for PHM very well.