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。     

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。     

利用试验数据的产品可靠性综合验证方案确定方法

常用抽样检验的方法进行产品可靠性验证,根据这一方法所确定的验证试验方案,在一定的风险下所需样本量较大,有时在工程上是不可接受的。针对这一问题,提出利用产品研制期间的试验数据,重新确定抽样方案,从而减少验证试验所需样本量或降低风险。由于这种方法充分利用了产品研制期间的试验信息,因此在保证有较好的验证效果的条件下,与传统的验证方案相比,可以减少试验样本量,降低风险。     

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。     

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%。      

机载武器作战使用可靠性综合验证

为减少机载武器可靠性验证试验样本量和降低验证试验风险,通过对机载武器作战使用可靠性验证的工程需求、试验方案、统计模型、验证方法等进行研究,提出了一种利用研制试验数据和定型飞行试验数据的作战使用可靠性综合验证方法。针对机载武器的特点,根据变动统计理论,考虑性能验证与可靠性验证的要求,综合利用研制试验数据和定型飞行试验数据,给出作战使用可靠性综合验证方案,进而制定设计定型飞行试验方案。实例表明,在不改变生产方风险和使用方风险的情况下,该方法可有效地验证机载武器挂飞可靠性和自主飞行可靠性指标,显著地减少定型飞行试验样本量,大幅节约研制成本,并缩短研制周期。     

基于Bayes变动统计理论的测试性外场统计验证方法

针对故障检测/隔离数据为"小子样"情况导致的测试性外场统计验证存在的周期长、验证结论置信度低等问题,研究并提出了基于Bayes变动统计理论的的测试性外场统计验证模型和方法。首先建立了不同寿命周期阶段故障检测率(FDR)的序化关系模型;然后以Dirichlet分布为先验分布,利用不同寿命周期阶段故障检测率先验估计值确定Dirichlet分布参数;在此基础上,融合"小子样、异总体"研制阶段增长试验数据和"小子样"外场使用数据,研究并提出了故障检测率的Bayes综合评估模型;引入Gibbs抽样方法求解故障检测率Bayes综合评估模型的复杂高维后验积分;最后在某机载稳定跟踪平台上开展了应用研究。结果表明本文方法能在较短的外场使用周期内,给出较高置信度的外场验证结论,为大型高可靠性装备测试性外场统计验证研究提供了重要的理论依据。     

基于Bayes理论的小子样维修性验证方法研究

针对现有经典维修性指标验证方法的不足,提出了一种小子样的维修性验证方法,即采用Bayes理论对维修性指标进行验证.给出了应用该方法的一般步骤,探讨了维修时间总体分布的确定方法,采用随机加权法对验前分布进行确定并利用ML - Ⅱ方法实现了多源信息的融合;进一步分析推导了基于Bayes理论的维修性验证方法的检验判据和样本量的大小.最后通过实例分析表明,该方法通过综合利用各种验前信息,可以有效地降低现场试验样本量,节省试验投入,缩短试验周期,且能保证较高的可信度.     

基于试验的试飞阶段检测率验证模型研究

针对某型运输机、预警指挥机等多个新型号的研制总要求提出的检测率指标,明确规划了相应的测试性摸底、测试性验证等试验。鉴于产品在整个试飞阶段会产生自然故障样本,从型号测试性验证的任务需求和GJB2547A最新要求出发,构建了测试性模拟试验样本的选取及分配原则、自然样本和模拟样本融合方法以及基于故障率的故障检测率验证模型,解决了传统测试性评估方法在实际应用中的样本覆盖不全以及评估结果受限等技术问题。     

机电产品寿命与可靠性综合验证试验技术研究

 大量机电产品既有可靠性指标要求,又有寿命指标要求,且在研制阶段结束时,需通过试验给出两种指标的验证结果。在对寿命与可靠性综合验证试验的可行性研究的基础上,提出了对其可靠性与寿命指标同时进行综合验证的试验方案。主要介绍该试验方案中的关键内容 :试验时间、失效 (故障 )判据、试验接收与拒收的判决准则的确定、试验结果的评估方法等。该试验方案的应用,为部分机电产品的寿命与可靠性试验验证提供了一个合理的、高效费比的技术途径。     

A Fault Sample Simulation Approach for Virtual Testability Demonstration Test

Virtual testability demonstration test has many advantages,such as low cost,high efficiency,low risk and few restrictions.It brings new requirements to the fault sample generation.A fault sample simulation approach for virtual testability demonstration test based on stochastic process theory is proposed.First,the similarities and differences of fault sample generation between physical testability demonstration test and virtual testability demonstration test are discussed.Second,it is pointed out that the fault occurrence process subject to perfect repair is renewal process.Third,the interarrival time distribution function of the next fault event is given.Steps and flowcharts of fault sample generation are introduced.The number of faults and their occurrence time are obtained by statistical simulation.Finally,experiments are carried out on a stable tracking platform.Because a variety of types of life distributions and maintenance modes are considered and some assumptions are removed,the sample size and structure of fault sample simulation results are more similar to the actual results and more reasonable.The proposed method can effectively guide the fault injection in virtual testability demonstration test.     

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.     

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。     

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.     

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。     

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.     

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。