Optimal Design of Multiple Stress Constant Accelerated Life Test Plan on Non-rectangle Test Region

For optimal design of constant stress accelerated life test（CSALT） with two-stress, if the stresses could not reach the highest levels simultaneously, the test region becomes non-rectangular. For optimal CSALT design on non-rectangle test region, the present method is only focused on non-rectangle test region with simple boundary, and the optimization algorithm is based on experience which can not ensure to obtain the optimal plan. In this paper, considering the linear-extreme value model and the optimization goal to minimize the variance of lifetime estimate under normal stress, the optimal design method of two-stress type-I censored CSALT plan on general non-rectangular test region is proposed. First, two properties of optimal test plans are proved and the relationship of all the optimal test plans is determined analytically. Then, on the basis of the two properties, the optimal problem is simplified and the optimal design method of two-stress CSALT plan on general non-rectangular test region is proposed. Finally, a numerical example is used to illustrate the feasibility and effectiveness of the method, The result shows that the proposed method could obtain the optimal test plan on non-rectangular test regions with arbitrary boundaries. This research provides the theory and method for two-stress optimal CSALT planning on non-rectangular test regions.

Optimal Design of Multiple Stresses Accelerated Life Test Plan Based on Transforming the Multiple Stresses to Single Stress

For planning optimum multiple stresses accelerated life test plans, a commonly followed guiding principle is that all parameters of the life-stress relationship should be estimated, and the number of the stress level combinations must be no less than the number of parameters of the life-stress relationship. However, the general objective of an accelerated life test（ALT） is to assess thep-th quantile of the product life distribution under normal stress. For this objective,estimating all model parameters is not necessary, and this will increase the cost of test. Based on the theoretical conclusion that the stress level combinations of the optimum multiple stresses ALT plan locate on a straight line through the origin of coordinate, it is proposed that a design idea of planning the optimum multiple stresses ALT plan through transforming the problem of designing an optimum multiple stresses ALT plan to designing an optimum single stress ALT plan. Moreover, a method of planning the optimum multiple stresses ALT plan which can avoid estimating all model parameters is established. An example shows that, the proposed plan which only has two stress level combinations could achieve an accuracy no less than the traditional plan, and save the test time and cost on one stress level combination at least; when the actual product life is less than the design value, even the deviation of the model initial parameters value is up to 20%, the variance of the estimation of thep-th quantile of the proposed plan is still smaller than the traditional plans approximately 25%. A design method is provided for planning the optimum multiple stresses ALT which uses the statistical optimum degenerate test plan as the optimum multiple stresses accelerated life test plan.

Design of Accelerated Life Test Plans——Overview and Prospect

Accelerated life test(ALT) is currently the main method of assessing product reliability rapidly, and the design of efficient test plans is a critical step to ensure that ALTs can assess the product reliability accurately, quickly, and economically. With the promotion of the national strategy of civil-military integration, ALT will be widely used in the research and development(R&D) of various types of products, and the ALT plan design theory will face further challenges. To aid engineers in selecting appropriate theories and to stimulate researchers to develop the theories required in engineering, with focus on the demands for theory research that arise from the implementation of ALT, this paper reviews and summarizes the development of ALT plan design theory. The development of the theory and method for planning optimal ALT for location-scale distribution, which is the most applied and mature theory of designing the optimal ALT plan, are described in detail. Taking this as the center of radiation, some problems that ALT now faces, such as the verification of the statistical model, limitation of sample size, solutions of resource limits, optimization of the test arrangement, and management of product complexity, are discussed, and the general ideas and methods of solving these problems are analyzed. Suggestions for selecting appropriate ALT plan design theories are proposed, and the urgent solved theory problems and opinions of their solutions are proposed. Based on the principle of convenience for engineers to select appropriate methods according to the problems found in practice, this paper reviews the development of optimal ALT plan design theory by taking the engineering problems arising from the ALT implementation as the main thread, provides guidelines on selecting appropriate theories for engineers, and proposes opinions about the urgent solved theory problems for researchers.

A Planning Method for Operational Test of UAV Swarm Based on Mission Reliability

The unmanned aerial vehicle(UAV)swarm plays an increasingly important role in the modern battlefield,and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm.Due to the high cost and long duration of operational tests,it is essential to plan the test in advance.To solve the problem of planning UAV swarm operational test,this study considers the multi-stage feature of a UAV swarm mission,composed of launch,flight and combat stages,and proposes a method to find test plans that can maximize mission reliability.Therefore,a multi-stage mission reliability model for a UAV swarm is proposed to ensure successful implementation of the mission.A multi-objective integer optimization method that considers both mission reliability and cost is then formulated to obtain the optimal test plans.This study first constructs a mission reliability model for the UAV swarm in the combat stage.Then,the launch stage and flight stage are integrated to develop a complete PMS(Phased Mission Systems)reliability model.Finally,the Binary Decision Diagrams(BDD)and Multi Objective Quantum Particle Swarm Optimization(MOQPSO)methods are proposed to solve the model.The optimal plans considering both reliability and cost are obtained.The proposed model supports the planning of UAV swarm operational tests and represents a meaningful exploration of UAV swarm test planning.

Efficient Penetration Testing Path Planning Based on Reinforcement Learning with Episodic Memory

Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test paths.In view of the difficulty for attackers to obtain complete network information in realistic network scenarios,Reinforcement Learning(RL)is a promising solution to discover the optimal penetration path under incomplete information about the target network.Existing RL-based methods are challenged by the sizeable discrete action space,which leads to difficulties in the convergence.Moreover,most methods still rely on experts’knowledge.To address these issues,this paper proposes a penetration path planning method based on reinforcement learning with episodic memory.First,the penetration testing problem is formally described in terms of reinforcement learning.To speed up the training process without specific prior knowledge,the proposed algorithm introduces episodic memory to store experienced advantageous strategies for the first time.Furthermore,the method offers an exploration strategy based on episodic memory to guide the agents in learning.The design makes full use of historical experience to achieve the purpose of reducing blind exploration and improving planning efficiency.Ultimately,comparison experiments are carried out with the existing RL-based methods.The results reveal that the proposed method has better convergence performance.The running time is reduced by more than 20%.

Optimum design of equivalent accelerated life testing plans based on proportional hazards-proportional odds model

The optimum design of equivalent accelerated life testing plan based on proportional hazards-proportional odds model using D-optimality is presented. The defined equivalent test plan is the test plan that has the same value of the determinant of Fisher information matrix. The equivalent test plan of step stress accelerated life testing （SSALT） to a baseline optimum constant stress accelerated life testing （CSALT） plan is obtained by adjusting the censoring time of SSALT and solving the optimization problem for each case to achieve the same value of the determinant of Fisher information matrix as in the baseline optimum CSALT plan. Numer- ical examples are given finally which demonstrate the equivalent SSALT plan to the baseline optimum CSALT plan reduces almost half of the test time while achieving approximately the same estimation errors of model parameters.

Planning failure-censored constant-stress partially accelerated life test

This article deals with the case of the failure-censored constant-stress partially accelerated life test （CSPALT） for highly reliable materials or products assuming the Pareto distribution of the second kind. The maximum likelihood （ML） method is used to estimate the parameters of the CSPALT model. The performance of ML estimators is investigated via their mean square error. Also, the average confidence interval length （IL） and the associated co- verage probability （CP） are obtained. Moreover, optimum CSPALT plans that determine the optimal proportion of the test units al- located to each stress are developed. Such optimum test plans minimize the generalized asymptotic variance （GAV） of the ML estimators of the model parameters. For illustration, Monte Carlo simulation studies are given and a real life example is provided.

Step-stress accelerated degradation test planning based on Wiener processwith correlation

To assess the lifetime distribution of highly reliable or expensive product,one of the most commonly used strategies is to construct step-stress accelerated degradation test(SSADT)which can curtail the test duration and reduce the test cost.In reality,it is not unusual for a unit with a higher degradation rate which exhibits a more volatile degradation path.Recently,Ye,Chen,and Shen[(2015).A new class of Wiener process models for degradation analysis.Reliability Engineering and System Safety,139,58–67]proposed a Wiener process to capture the positive correlation between the drift rate and the volatility.In this paper,an optimal SSADT plan is developed under the assumption that the underlying degradation path follows the Wiener process with correlation.Firstly,the stochastic diffusion process is introduced to model a typical SSADT problem.Then the design variables,including the sample size,the measurement frequency and the numbers of measurements under each stress level,are optimised by minimising the asymptotic variance of the estimated p-percentile of the product’s lifetime distribution subject to the total experimental cost not exceeding a pre-specified budget.Finally,a numerical example is presented to illustrate the proposed method.

Inference and optimal design on step-stress partially accelerated life test for hybrid system with masked data

Under Type-Ⅱ progressively hybrid censoring, this paper discusses statistical inference and optimal design on stepstress partially accelerated life test for hybrid system in presence of masked data. It is assumed that the lifetime of the component in hybrid systems follows independent and identical modified Weibull distributions. The maximum likelihood estimations(MLEs)of the unknown parameters, acceleration factor and reliability indexes are derived by using the Newton-Raphson algorithm. The asymptotic variance-covariance matrix and the approximate confidence intervals are obtained based on normal approximation to the asymptotic distribution of MLEs of model parameters. Moreover,two bootstrap confidence intervals are constructed by using the parametric bootstrap method. The optimal time of changing stress levels is determined under D-optimality and A-optimality criteria.Finally, the Monte Carlo simulation study is carried out to illustrate the proposed procedures.

Novel Accelerating Life Test Method and Its Application by Combining Constan Stress and Progressive Stress

Constant stress accelerated life tests(ALTs) can be applied to obtain a high estimation accuracy of reliability measure?ments, but these are time?consuming tests. Progressive stress ALTs can yield failures more quickly but cannot guaran tee the estimation accuracy of reliability measurements. In this paper, a progressive?constant combination stress ALT is proposed to combine the merits of both tests. The optimal plan, in which the design variables are the initial pro?gressive stress level, the progressive stress ramp rate, the sample allocation proportion of the progressive stress and the constant stress level, is determined using the principle of minimizing the asymptotic variance of the maximum likelihood estimator of the natural log reliable life for the connectors. A comparison between the optimal PCCSALT plan and the CSALT plan with the same sample size and estimation accuracy shows that the test time is reduced by 13.59% by applying the PCCSALT.

Airtest平台自动化测试方案设计与实现

为改善传统移动端自动化测试方案控件覆盖率低,不同操作系统脚本之间不兼容且复用率低的缺点,提出一种基于蚁群算法的全路径最优规划算法。首先通过深度优先搜索算法对界面控件预处理,然后逐一遍历获取控件信息合并冗余控件,最后结合改进的蚁群算法生成测试用例。基于该算法提出一种自动化测试方案,在Airtest自动化测试平台上进行测试并在移动端平台进行验证。结果表明:该方案前期快速收敛,测试控件,达到85%的覆盖率,比基于录制回放测试方案提高了3倍且兼容多个操作平台,显示该方案在兼容性以及测试可信度上均有优势。

General Consideration of Measuring System for Operational Test of Thyristor Valves of Ultra High Voltage DC Power Transmission

Thyristor valve is one of the key equipments for ultra high voltage direct current(UHVDC) power transmission projects.Before being installed on site,they need to be tested in a laboratory in order to verify their operational performance to satisfy the technical specification of project related.Test facilities for operational tests of thyristor valves are supposed to enable to undertake more severe electrical stresses than those being applied in the thyristor valves under test(test objects).On the other hand,the stresses applied into the test objects are neither higher nor lower than specified by the specification,because inappropriate stresses applied would result in incorrect evaluation of performance on the test objects,more seriously,would cuase the damage of test objects with expensive cost losing.Generally,the process of operational tests is complicated and performed in a complex synthetic test circuit(hereafter as STC),where there are a lot of sensors used for measuring,monitoring and protection on line to ensure that the test circuit functions in good condition.Therefore,the measuring systems embedded play a core role in STC,acting like "eyes".Based on the first project of building up a STC in China,experience of planning measuring systems is summarized so as to be referenced by related engineers.

Depth Estimates of Buried Utility Systems Using the GPR Method: Studies at the IAG/USP Geophysics Test Site

Identifying underground utilities and predicting their depth are fundamental when it comes to civil engineering excavations, for example, to install or repair water, sewer, gas, electric systems and others. The accidental rupture of these systems can lead to unplanned repair costs, delays in completing the service, and risk injury or death of workers. One way to detect underground utilities is using the GPR-Ground Penetrating Radar geophysical method. To estimate depth, the travel time (two-way travel time) information provided by a radargram is used in conjunction with ground wave velocity, which depends on the dielectric constant of materials, where it is usually assumed to be constant for the area under investigation. This procedure provides satisfactory results in most cases. However, wrong depth estimates can result in damage to public utilities, rupturing pipes, cutting lines and so on. These cases occur mainly in areas that have a marked variation of water content and/or soil lithology, thus greater care is required to determine the depth of the targets. The present work demonstrates how the interval velocity of Dix (1955) can be applied in radargram to estimate the depth of underground utilities compared to the conventional technique of constant velocity applied to the same data set. To accomplish this, synthetic and real GPR data were used to verify the applicability of the interval velocity technique and to determine the accuracy of the depth estimates obtained. The studies were carried out at the IAG/USP test site, a controlled environment, where metallic drums are buried in known positions and depths allowing the comparison of real to estimated depths. Numerical studies were also carried out aiming to simulate the real environment with variation of dielectric constant in depth and to validate the results with real data. The results showed that the depths of the targets were estimated more accurately by means of the interval velocity technique in contrast to the constant velocity technique, minimizing the risks of accidents during excavation.

Validation of Treatment Planning Dose Calculations: Experience Working with Medical Physics Practice Guideline 5.a.

Recently published Medical Physics Practice Guideline 5.a. (MPPG 5.a.) by American Association of Physicists in Medicine (AAPM) sets the minimum requirements for treatment planning system (TPS) dose algorithm commissioning and quality assurance (QA). The guideline recommends some validation tests and tolerances based primarily on published AAPM task group reports and the criteria used by IROC Houston. We performed the commissioning and validation of the dose algorithms for both megavoltage photon and electron beams on three linacs following MPPG 5.a. We designed the validation experiments in an attempt to highlight the evaluation method and tolerance criteria recommended by the guideline. It seems that comparison of dose profiles using in-water scan is an effective technique for basic photon and electron validation. IMRT/VMAT dose calculation is recommended to be tested with some TG-119 and clinical cases, but no consensus of the tolerance exists. Extensive validation tests have provided the better understanding of the accuracy and limitation of a specific dose calculation algorithm. We believe that some tests and evaluation criteria given in the guideline can be further refined.

面向智能航行避碰决策与规划的虚拟仿真测试技术研究

研究了面向智能航行避碰决策与规划的虚拟仿真测试技术。介绍了智能航行在货运船舶中的应用需求,分析了当下避碰决策策略、路径规划算法以及避碰决策与规划测试技术的研究现状。面向货运船舶智能航行避碰决策与规划能力,基于避碰规则中的会遇态势划分,结合四元船舶领域和贝塞尔曲线插值理论,提出了一种智能航行避碰决策与规划算法。构建了一种基于虚拟仿真环境的避碰决策与规划算法仿真测试方法,通过AIS(automatic identification system)模拟器模拟目标船的状态数据,结合船载综合导航系统(integrated navigation system,INS)实现了避碰决策与规划算法的测试。通过复杂水域仿真测试验证了所提算法的有效性和可行性,为货运船舶智能航行功能的开发与实践提供了参考。

铜冶炼熔炼渣贫化工艺试验

针对铜冶炼渣性质特点,对渣中铜、铅、锌、铁的赋存状态进行分析,制定了优化试验方案,在小型试验研究的基础上,开展了工业试验研究,实现炉渣原矿品位:Cu 1.699%、Au 0.358 g/t、Ag 29.786 g/t;铜精矿含Cu品位18.662%,含Au 2.81g/t,含Ag 64.705 g/t;铜精矿中Cu实际回收率79.494%,Au实际回收率59.612%,Ag实际回收率71.597%;尾矿中含Cu 0.366%。

钠冷快堆组件编码自动识别装置的试验研究及应用

为保证钠冷快堆入堆组件的正确性,本文设计将组件编号转换为二维码并标记在组件上,在新组件转运设备上安装读码设备,通过读码设备对入堆新组件编码进行自动识别,将组件编码转换为组件编号并通过通讯传递至燃料操作监控系统。监控系统将其与换料计划中的组件编号进行比较,可判断转运的入堆新组件是否正确,提高组件操作的可靠性和安全性。为确定组件编码的各项技术参数,通过枚举法分析并总结了影响组件编码识别的各种因素,确定出单一因素试验方案,最终通过各种参数与功能试验,获得了适用于大型快堆电站组件编码自动识别装置的组件编码各项参数,试验结果证明研发目标完全实现。

融合改进哈里斯鹰和改进动态窗口的机器人动态路径规划

针对动态环境的移动机器人路径规划问题,提出了一种改进哈里斯鹰算法(IHHO)与改进动态窗口算法(IDWA)的融合算法(IHHO-IDWA)。首先,针对哈里斯鹰算法后期搜索性能不足等问题,提出了融合自适应混沌和核心种群动态划分策略、融合黄金正弦策略以及动态云最优解扰动策略来提高算法的性能。其次,针对动态窗口算法存在规划的路径长和易陷入死锁等问题,提出了三个改进策略:增加子函数,保证算法能够规划出更短的路径;提出自适应权重策略,平衡算法局部避障能力和全局搜索性能;设定初始航向角,避免路径冗余。最后,通过测试函数、CEC2014函数的数值实验和静态、动态路径规划实验,验证了IHHO和IDWA性能有明显提升;通过50×50大型动态地图验证了融合算法较对照组算法规划的路径缩短了11.51%,证明了该方法的优越性。

融合模式搜索的蝗虫优化算法及其应用

在智能优化算法应用于复杂优化问题的求解过程中,平衡开发和探索以获得最优解具有重要意义。因此针对传统蝗虫优化算法在处理一些较为复杂的优化问题时出现的收敛精度低、搜索能力弱且容易陷入局部最优等缺陷,提出一种融合模式搜索的蝗虫优化算法。首先引入Sine混沌映射初始化蝗虫个体种群位置,减少个体重叠概率以增强种群迭代初期的多样性;其次利用模式搜索法,对种群目前找到的最优目标展开局部搜索,提高算法的收敛速度与寻优精度;同时为了避免算法后期陷入局部最优,引入了基于凸透镜成像的反向学习策略。实验部分通过对改进的蝗虫算法进行消融实验,验证了Sine混沌映射、模式搜索、反向学习每个策略的独立有效性。并用两组测试函数进行仿真实验,采用Wilcoxon秩和检验、Friedman检验的方法进行结果分析。实验结果均表明了融合模式搜索法改进的蝗虫算法在收敛速度与寻优精度上得到明显提高。最后,将其应用于移动机器人路径规划,测试结果进一步验证了改进算法的有效性。

无人机检测桥梁多目标点路径规划方法研究

针对无人机检测桥梁下部结构多目标点路径规划问题,建立无人机检测桥梁墩柱的数字模型.利用改进后的Henon混沌映射对传统人工蜂群算法(ABC算法)中的蜜源初始化阶段和侦察蜂搜索阶段进行优化,提出了一种基于混沌映射改进后的ABC算法(HABC算法),通过仿真对比分析发现HABC算法相较于ABC算法迭代收敛更快,平均评价函数值也优于ABC算法,实现全局路径规划问题中算法的优化.将HABC算法和贪心策略相结合提出一种贪心HABC算法,实现UAV检测桥梁墩柱结构多目标点路径规划,通过仿真验证了算法的可靠性.结果显示通过牺牲少量路径总长度可有效节省算法运行时间.