多信号模型故障模式与信号概率关联算法

为适应复杂装备的测试性建模,多信号模型采用层次化的建模方式.针对建模过程中信号概率和故障模式(功能故障和完全故障)概率的冲突问题,提出了三种概率关联更新算法,并通过某装备模块多信号模型的故障模式及信号概率的更新验证了算法的有效性.算法提高了测试性分析与评估的精度,为模型的修正和故障诊断策略的生成提供了更加可靠的依据.     

测试性建模与分析中的故障概率获取方法研究

在实际维修测试中,为了系统安全和减少测试时间,经常采用模块化诊断和模糊组替换诊断等含有实用特性的故障诊断方法.在测试性建模、分析与评估和诊断策略的设计中,对于采用含实用特性诊断方法的系统而言,传统的故障概率计算方法不再适用,提出了基于蒙特卡罗仿真的故障概率获取方法.仿真分析表明,利用该方法得到的故障率更加真实可靠,能为测试性建模、分析和诊断策略的设计提供更加准确的依据.     

基于多信号模型的系统测试性建模与分析

多信号模型是一种简单而有效的系统建模表示方法,已被美国QSI公司引入其TEAMS(测试性工程和维修系统)软件中,用于系统测试性分析和预计、可靠性分析以及故障诊断等。对基于多信号模型的系统测试性建模与分析方法进行深入研究,结合示例具体给出多信号模型的表示和建模,故障-测试相关矩阵以及未检测故障、模糊组、冗余测试、故障掩盖、故障检测率和故障隔离率等的具体分析过程和算法。算法分析结果与应用TEAMS软件分析结果相一致。基于多信号模型的测试性分析方法,虽然不能给出一个全面的测试性评定结论,并存在着不足之处亟待改进,但易于实现计算机辅助分析,对系统测试性设计工具的研发具有价值。     

基于贝叶斯网络的系统测试性建模与分析

针对现有测试性建模方法对系统不确定信息描述及分析上的不足,提出了基于贝叶斯网络的测试性建模与分析方法。首先结合贝叶斯网络的基本理论,阐述了系统测试性模型的构成要素及建立流程,用相关性矩阵表示系统故障-测试之间的关联,用条件概率矩阵描述两者间的不确定信息;然后给出了测试性指标的具体分析过程和算法;最后通过实例验证了方法的有效性。     

基于多信号模型的舰船柴油机测试性研究

从设计着手,全系统全寿命周期考虑装备的测试诊断问题是避免重大事故发生和降低维修保障费用的有效手段.在充分研究舰船柴油机测试性特点及现状的基础上,引入多信号模型对舰船柴油机的润滑系统进行了测试性建模与分析,对其测试性设计提出了改进措施,能够全面地检测与隔离故障,为科学合理的制定测试方案提供了方法指导.     

基于TEAMS的惯性测量组合测试性建模与分析

惯性测量组合(IMU)是飞行器控制系统中的核心部件,其结构复杂、精度要求高,是故障率最高的部件之一。基于TEAMS平台建立某惯组系统的多信号模型,并对其测试性进行分析与评估,针对固有测试在故障定位和诊断中存在的不足,提出两种测试点的改进方案。分析结果表明:改进后的IMU测试性得到了显著提高,基于多信号模型的测试性分析与评估方法对增强装备保障能力是有效的。     

基于使用方的火控系统的测试性研究

测试性研究已经成为火控系统发展的一个方向.本文分析了装甲装备火控系统可测试性和可维修性的现状,针对目前装甲装备火控系统的测试性与设计、制造分离的状态,提出必须实施系统的测试性设计.针对国内外装甲装备的测试性技术的发展和火控系统的复杂性及在装甲装备上的特殊地位,具体探讨了坦克火控系统的测试性指标和机内测试(BIT)技术的发展.     

基于改进熵权的属性综合评价模型在雷达BIT测试性能评估中的应用

针对目前雷达装备BIT缺乏全面有效的测试性综合评价的问题,提出基于属性综合评价法的雷达BIT测试性综合评价模型。首先建立雷达装备BIT测试特性指标,然后以熵权系数法修正层次分析法的权重为基础,应用属性综合评价系统对某型雷达装备BIT系统进行建模分析,得到综合评价结果,对雷达BIT测试性评估研究具有参考价值。     

装备测试性设计与诊断策略优化技术研究

该研究从复杂装备的诊断测试出发,对装备层次的测试性建模进行了探讨,包括测试性建模要素分析和层次测试性建模;介绍了装备测试诊断技术的发展历程、发展趋势。对其测试诊断策略的优化进行了深入而详细地分析,对目前国内外普遍使用的算法和设计方法进行了介绍,比较了上述方法的使用范围、优缺点。最后举例分析了装备测试性设计与诊断策略优化技术的实际应用范围、产生的问题,展望了测试诊断优化技术的发展趋势。     

论航空装备的测试性与计量及计量性设计

分析了测试与计量的关系及测试设备的计量特性;论述了BITE,ATE等设备的计量需求;以装备研制过程贯彻计量性设计为主线,分析了计量性设计的工作内容及BITE和ATE的计量性设计策略,从理论上为装备测试的可计量提供支持。     

Test sample allocation method for testability verification test

An extended failure mode effect and criticality analysis (FMECA)-based sample allocation method for testability verification is presented in this study to deal with the poor representativeness of test sample sets and the randomness of the testability evaluation results caused by unreasonable selection of failure samples. First, the fault propagation intensity is introduced as part of the extended information of FMECA, and the sample allocation impact factors of component units and failure modes are determined under this framework. Then, the failure mode similarity and impact factor support are defined, and the game decision method for weighing the relationship between similarity and support is proposed to obtain the weight of failure mode impact factor. Finally, a two-step allocation framework of test samples is formulated to realize the sample allocation of component units and failure modes. This method is applied to the testability verification test of a launch control system. Results show that this method can obtain more representative test samples compared with the traditional sample allocation method while effectively reducing randomness of single testability evaluation result.     

Error-based stopping criterion for the combined adaptive Kriging and importance sampling method for reliability analysis

Metamodel-based method is a wise reliability analysis technique because it uses the metamodel to substitute the actual limit state function under the predefined accuracy. Adaptive Kriging (AK) is a famous metamodel in reliability analysis for its flexibility and efficiency. AK combined with the importance sampling (IS) method abbreviate as AK–IS can extremely reduce the size of candidate sampling pool in the updating process of Kriging model, which makes the AK-based reliability method more suitable for estimating the small failure probability. In this paper, an error-based stopping criterion of updating the Kriging model in the AK–IS method is constructed and two considerable maximum relative error estimation methods between the failure probability estimated by the current Kriging model and the limit state function are derived. By controlling the maximum relative error, the accuracy of the estimate can be adjusted flexibly. Results in three case studies show that the error-based stopping criterion based AK–IS method can achieve the predefined accuracy level and simultaneously enhance the efficiency of updating the Kriging model.     

A corrective maintenance scheme for engineering equipment

Corrective maintenance is a maintenance task performed to identify and rectify the cause failures for a failed system. The engineering equipment gets many components and failure modes, and its failure mechanism is very complicated. Failure of system-level might occur due to failure(s) of any subsystem/component. Thus, the symptom failure of equipment may be caused by multilevel causality of latent failures.This paper proposes a complete corrective maintenance scheme for engineering equipment. Firstly, the FMECA is extended to organize the numerous failure modes. Secondly, the failure propagation model (FPM) is presented to depict the cause-effect relationship between failures. Multiple FPMs will make up the failure propagation graph (FPG). For a specific symptom failure, the FPG is built by iteratively searching the cause failures with FPM. Moreover, when some failure in the FPG is newly ascertained to occur (or not), the FPG needs to be adjusted. The FPG updating process is proposed to accomplish the adjustment of FPG under newly ascertained failure. Then, the probability of the cause failures is calculated by the fault diagnosis process. Thirdly, the conventional corrective maintenance recommends that the failure with the largest probability should be ascertained firstly. However, the proposed approach considers not only the probability but also the failure detectability and severity. The term REN is introduced to measure the risk of the failure. Then, a binary decision tree is trained based on REN reduction to determine the failure ascertainment order. Finally, a case is presented to implement the proposed approach on the ram feed subsystem of a boring machine tool. The result proves the validity and practicability of the proposed method for corrective maintenance of engineering equipment.     

电路板TPS验证与评估方法研究

用TPS对电路板进行自动测试、对电路板进行故障检测和修理,是提高新装备维修保障能力的关键。首先结合TPS评估与验收的需求,给出了电路板TPS验证的主要内容;然后介绍了基于故障注入的电路板TPS验证评估方法;在物理模拟故障注入样本集的充分性验证中,利用了基于多信号模型的测试模型建模方法,提高了验证准确性和效率。