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非完美测试条件下的测试性设计理论与方法研究

Research on the Theory and Method of Testability Design with Imperfect Tests

【作者】 张士刚

【导师】 温熙森;

【作者基本信息】 国防科学技术大学 , 机械工程, 2013, 博士

【摘要】 测试性设计对降低装备的全寿命周期费用、提高装备的故障诊断性能、保证装备的安全运行具有重要的意义。然而,随着测试性工程逐步深入应用于空间站等复杂装备,当前以完美测试(perfect test)假设(0-1相关性)为基础的测试性设计理论暴露出不少的问题。比如:在设计阶段未对诊断时效性进行评估和优化设计,使得系统可能存在一定的设计缺陷;测试性理论对工程中存在的测试不可靠和时延等因素考虑不够充分,导致所构建的诊断系统虚警率和漏检率普遍偏高;基于现有测试性理论构建序贯诊断策略的过程中仅针对测试执行费用进行序列优化,使得维修诊断策略全寿命周期费用偏高。测试性工程应用中存在的上述问题,主要是由于现有测试性设计过程的完美测试假设以及相关的建模、分析、推理方法与实际工程问题不完全匹配,进行了不合理简化造成的。为此,本文针对上述问题系统研究了非完美测试条件下的测试性设计理论和方法。在此,非完美测试(imperfect test)指的是针对确定的故障状态,测试结果(正常或异常)不确定或与时间相关的测试。与测试性设计流程一致,论文研究围绕非完美测试条件下的测试性建模、测试优化选择、动态故障诊断、序贯诊断等关键问题展开,对非完美测试条件下的测试性设计理论和方法进行了探索。具体包括:(1)研究了非完美测试条件下的测试性建模和信息描述方式,实现了测试不可靠、时延、故障耦合传播等信息的有效表达,为后续测试性设计工作的开展奠定了基础。(2)提出了非完美测试条件下的测试性评价指标计算方法,研究了非完美测试的优化选择问题,对其进行了数学描述,提出采用遗传算法和拉格朗日松弛算法进行求解。针对遗传算法,设计了整体计算流程,提出了生成可行解的启发式方法,对测试不可靠、时延、多值、非独立费用测试等各种非完美测试情形下的测试选择问题进行了详细论述。针对拉格朗日松弛算法,推导了问题分解策略,将原始问题划分为三个可解子问题进行求解。通过实例和仿真验证说明了两种方法的有效性和不同特点。(3)提出了含时延特性的动态耦合故障诊断推理(Delay Dynamic CoupledFaults Diagnosis, DDCFD)模型,有效克服了传统模型对测试不可靠、时延、故障耦合传播等因素表达能力不足而导致的虚警、漏检等问题。由于基于DDCFD模型的推理问题不具有可分解结构,提出了部分采样算法(Partial-sampling Algorithm)和分块坐标上升-维特比算法(Block Coordinate Ascent with the Viterbi Algorithm,BCV算法)进行诊断推理。在部分采样算法中,利用边界求解,有效减少了重复运算的次数,提高了推理速度。在分块坐标上升-维特比算法中,利用循环迭代策略简化了问题的求解,采用软状态的方式有效克服了局部最优的问题。针对高阶马尔可夫链的状态求解问题,推导了高阶维特比算法。通过仿真试验对所提的模型和算法进行了验证,得出了两种算法的特点,总结了不同参数对算法的影响。验证结果表明DDCFD模型以及两种推理算法可有效解决含时延及耦合特性的动态故障诊断推理问题,两种算法具有不同的特性,适用于具有不同长度时延的情形。(4)研究了面向全寿命周期的序贯诊断策略优化生成问题,对该问题的来源和内涵进行了阐述,并进行了数学推导。针对非完美测试一般情形和完美测试这一子情形提出了基于与或图搜索的算法,并提出了简化计算的策略。通过仿真实验及算法对比证明了所提算法生成的诊断策略优于传统方法生成的诊断策略,具有更低的全寿命周期费用。(5)以某航天器热控分系统为例对本文所提的非完美测试条件下的测试性设计有关理论方法进行了应用验证,系统实现了包含测试性建模、测试优化选择、动态故障诊断、序贯诊断的测试性设计技术流程,并与传统的基于完美测试假设所得的测试性设计结果进行了对比。结果表明,所提方法可有效实现非完美测试条件下的测试性设计,提高了诊断系统的诊断精度,减少了序贯诊断策略的全寿命周期费用。相关成果可推广应用于其它分系统和装备,在实现装备安全运行、高效保障上发挥重要作用。

【Abstract】 Testability design has an important significance in reducing life cycle cost of theequipment, improving the performance of the diagnostic systems and the guarantee ofequipment safe running. However, some problems are met when the testability theorybased on perfect test assumption (0-1dependency relationship) is applied to thecomplex equipment such as the space station. For example, the diagnostic timeliness isnot taken into account when designing the diagnostic systems, which may leads to theexistence of critical design defects in the equipment; false alarm rate and missingdetection rate are commonly high because the unreliability and latency of the tests is notfully considered; the optimal generation of the sequential fault diagnostic strategy isonly based on the execution cost of the tests, which may result in a high life cycle cost.The problems discussed above are basically caused by the unreasonable perfect testassumption and the testability modeling, analysis and inference method based on it. Inorder to resolve these problems, the testability design theory and method with imperfecttests is studied in this thesis, where imperfect tests denote those tests that are unreliableand have test latency. The research on testability modeling, test selection, dynamic faultdiagnosis and sequential fault diagnosis based on imperfect tests is carried out accordingto the design process of testability, which forms a whole testability design theoreticalsystem. The details of the content are as follows.(1) Testability modeling and information expression method based on imperfecttest assumption is proposed, where test delay, unreliable test and fault propagation canbe effectively modeled, which lay a good foundation for the consequential testabilitydesign process.(2) Testability evaluation method with imperfect tests is proposed. The imperfecttest selection problem is formulated. A genetic algorithm (GA) and a LagrangianRelaxation Algorithm (LRA) are proposed to solve the problem. A heuristic method togenerate the feasible solution in GA is formulated. GA is a general approach for solvingthe problem with imperfect tests including the scenarios with delayed and multiple testoutcomes, non-independent cost, et al. The LRA overcomes the computationalcomplexity of the primal optimization problem by decomposing it into three tractablesub-problems. Theoretical analysis and simulation experiments show that the twomethods are effective to solve the test selection problem, with different characteristics.(3) A delay dynamic coupled fault diagnosis (DDCFD) model to deal with theproblem of coupled fault diagnosis with fault propagation/transmission delays andobservation delays with imperfect test outcomes is proposed, which has the potential toreduce the false alarm rate and missing detection rate of the diagnostic systems. Sincethe faults are coupled, the problem does not have a decomposable structure. Consequently, we propose a Partial-sampling method and a method based on blockcoordinate ascent and the Viterbi algorithm (BCV) to deal with the coupled-stateproblem. By reducing the number of samples and avoiding redundant computations, thecomputation time of Partial-sampling method is substantially smaller than the regularAnnealed MAP method with no noticeable impact on diagnostic accuracy. This BCValgorithm reduces complexity by assuming all other faults to be constant from theprevious iteration when computing the state sequence of a component. Furthermore, thelocal maximum is escaped by using soft state relaxation. For the state estimationproblem of single Markov chain, a high order Viterbi algorithm is formulated. Finally,we test the inference algorithms proposed in this paper by applying them to systems ofdifferent complexity. Some conclusions are obtained, which indicate that the twomethods have different performances in different applying scenarios. They are suitablefor the systems with long delays and short delays, respectively.(4) The test sequencing problem considering life cycle cost is firstly addressed,which is formulated as a complex optimization problem. For the cases with imperfecttests and its special scenario that the tests are perfect, two algorithms and theirvariations reducing the computational time are proposed based on AND/OR graphsearch. Comparisons based on the simulation and the application results show that thediagnostic strategy generated by the proposed algorithms is better than the one obtainedby the traditional method, which has a lower life cycle cost.(5) The theory and method proposed in this thesis are applied on the thermalcontrol system of a spacecraft. The technical process consisting of testability modeling,test selection, dynamic fault diagnosis and sequential fault diagnosis based on imperfecttest assumption is realized. Meanwhile, the similar process is implemented using theexisting theory based on perfect test assumption. Comparisons are made, which indicatethat the proposed theoretical system has a better performance (e.g., more accuratereal-time diagnostic result, lower life cycle cost of the sequential fault diagnosticstrategy, et al.) in realizing testability design with imperfect tests. It has the greatpotential to be applied to other systems and equipment.

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