On the evidential reasoning rule for dependent evidence combination

Evidential Reasoning (ER) rule, which can combine multiple pieces of independent evidence conjunctively, is widely applied in multiple attribute decision analysis. However, the assumption of independence among evidence is often not satisfied, resulting in ER rule inapplicable. In this paper, an Evidential Reasoning rule for Dependent Evidence combination (ERr-DE) is developed. Firstly, the aggregation sequence of multiple pieces of evidence is determined according to evidence reliability. On this basis, a calculation method of evidence Relative Total Dependence Coefficient (RTDC) is proposed using the distance correlation method. Secondly, as a discounting factor, RTDC is introduced into the ER rule framework, and the ERr-DE model is formulated. The aggregation process of two pieces of dependent evidence by ERr-DE is investigated, which is then generalized to aggregate multiple pieces of non-independent evidence. Thirdly, sensitivity analysis is carried out to investigate the relationship between the model output and the RTDC. The properties of sensitivity coefficient are explored and mathematically proofed. The conjunctive probabilistic reasoning process of ERr-DE and the properties of sensitivity coefficient are verified by two numerical examples respectively. Finally, the practical application of the ERr-DE is validated by a case study on the performance assessment of satellite turntable system.     

民用飞机电传飞控系统功能危害性评估方法研究

民机系统级功能危害性评估（Functional Hazard Assessment, 简称FHA）是指对系统功能进行系统性的综合分析过程，即依据系统功能失效状态对飞机安全性影响严重程度进行评估，从而实现对功能的等级进行识别和分类的过程，是系统顶层关键的设计过程。在分析大量相关资料和实际型号经验的基础上，得出适用于民机电传飞控系统的功能定义、功能失效状态分析和确定功能失效影响等级并对其进行确认的思路和方法，以及保证民机电传飞控系统级FHA正确性和完整性的具体可行的措施等，该方法已应用到某民机电传飞控系统级FHA的评估工作中，取得了良好的效果。     

液体运载火箭爆炸冲击波近场危害性定量评估方法研究

嫦娥四号探测器首次采用了我国自主研制的同位素热源装置，为有效评估运载火箭发生爆炸后，爆炸冲击波对同位素热源装置的危害性，解决同位素热源装置安全设计指标确定难题，开展了液体运载火箭爆炸冲击波近场危害性的评估方法研究，提出了适用于液体运载火箭爆炸冲击波近场危害性评估的爆炸当量、爆炸冲击波峰值超压及作用时间的定量评估模型。     

Uncertainty-aware Cube algorithm for medium-term collision risk assessment

The number of Earth orbiting objects is constantly growing, and some orbital regions are becoming risky environments for space assets of interest, which are increasingly threatened by accidental collisions with other objects, especially in Low-Earth Orbit (LEO). Collision risk assessment is performed by various methods, both covariance and non-covariance based. The Cube algorithm is a non-covariance-based method used to estimate the collision rates between space objects, whose concept consists in dividing the space in cubes of fixed dimension and, at each time instant, checking if two or more objects share the same cube. Up to now its application has been limited to the long-term scenarios of orbital debris evolutionary models, where considering the uncertainties is not necessary and impractical. Within operative contexts, instead, medium-term collision risk analysis may be an important task, in which the propagation-related uncertainties play a prominent role, but the timescale poses challenges for the application of standard covariance-based conjunction analysis techniques. In this framework, this paper presents an approach for the evaluation of the medium-term collision frequency for objects in LEO, called Uncertainty-aware Cube method. It is a modified version of the Cube, able to take the possible errors in the space objects’ position into account for the detection of the conjunctions. As an object’s orbit is propagated, the along-track position error grows more and more, and each object could potentially be in a different position with respect to the one determined by numerical propagation and, thus, in a different cube. Considering the uncertainties, at each time instant the algorithm associates more than one cube to each object and checks if they share at least one cube. If so, a conjunction is detected and a degree of confidence is evaluated. The performance of the method is assessed in different LEO scenarios and compared to the original Cube method.     

涡轮榫接疲劳寿命评估及验证：研究现状及展望

介绍了涡轮榫接结构疲劳寿命评估技术的研究现状，分别从多场载荷分析、裂纹萌生寿命评估、裂纹扩展模拟和试验技术等方面探讨了现有研究的进展、不足以及发展趋势，重点论述了涡轮榫接结构使用寿命和损伤容限的评估方法。结果表明：现有的分析和试验方法能基本实现涡轮榫接的疲劳寿命评估，但由于各种局限性，工程适用性亟待提高，仍需稳健的载荷降阶分析方法、基于物理机制和数据驱动的寿命评估方法、载荷历程相关的裂纹扩展寿命评估方法和复杂热力环境下的试验技术，从而建立先进航空发动机涡轮榫接结构疲劳寿命评估及验证体系。     

基于任务协同的有人机/无人机 对海攻击作战效能评估研究

通过分析攻击敌海上舰船目标过程中有人机/无人机编队的作战使用方式及影响其作战效能的主要因素,建立了有人机/无人机编队协同攻击海上目标的作战效能评估指标体系,运用ADC法构建了有人机/无人机混合编队攻击敌舰船目标作战效能评估模型,通过算例证明了该方法适应于有人机/无人机编队的作战效能评估,为有人机/无人机协同作战决策提供了有效的参考依据。     

民用飞机验证类试验/试飞中构型差异管理策略研究

在民用飞机研发过程中,构型差异管理是适航验证类试验/试飞过程中进行的必要动作,用以评估当前设计构型能否满足试验/试飞进行的要求以及试验/试飞的适航代表性。从单机设计构型要求、适航验证类试验/试飞要求、型号设计构型、单机设计构型以及实物状态的角度出发,分析了适航验证类试验前后飞机的各类构型差异,并提出了构型差异管理模型。     

于不确定性与重要度的改进DSmT健康状态评估

针对目前健康状态评估准确度不高、客观性不强的问题,引入评估指标的不确定性和重要度,提出一种基于不确定性和重要度的改进DSmT（Dezert Smarandache theory）健康状态评估方法.首先,引入指标不确定性和重要度作为加权因子,能够得到比较合理的指标权重；其次,采用模糊综合评判方法,通过构造三角形梯形隶属度函数确定各指标的广义基本信度赋值；然后,基于指标权重对广义基本信度赋值进行改进DSmT融合,得到各指标的广义基本信度赋值加权融合后的评估结果；最后,以某供电系统为例进行了实例验证,结果表明该方法能够赋予各评估指标较合理的权重,健康状态评估结果与系统实际运行状态相符.      

面向有效载荷的准实时在轨健康评估系统

卫星遥测数据通常有2种手段获得，一种是卫星经过地面测控站下传的实时遥测和延时遥测;另一种手段是通过数传分系统下传的全球遥测。全球遥测作为监视卫星载荷健康状态的主要手段，存在数据量大、文件数量较多、人工处理和判读工作量大等问题。针对该情况，提出准实时在轨健康监视系统的设计方案。该系统具备遥测源码定时获取、有效载荷遥测数据提取和解析、遥测数据存储、遥测数据自动判读和特征统计、超限报警、曲线显示和数据输出等功能，可对卫星有效载荷的健康状态进行准实时、自动化的监视和评估。     

Synthetic damage effect assessment through evidential reasoning approach and neural fuzzy inference: Application in ship target

The damage effect assessment of anti-ship missiles combines system science and weapon science, which can provide reference for the assessment of battlefield damage situation. In order to solve the difficulty of heterogeneous data aggregation and the difficulty in constructing the mapping between factors and damage effect, this paper analyzes the specific damage process of the anti-ship missile to the ship, and proposes a synthetic Evidential Reasoning (ER) – Adaptive Neural Fuzzy Inference System (ANFIS) to assess the damage effect. To solve the problem of fuzziness and uncertainty of criteria in the assessment process, the belief structure model is used to transform qualitative and quantitative information into a unified mathematical structure, and ER algorithm is used to fuse the information of lower-level criteria. In order to solve the problem of fuzziness and uncertainty of the information contained in the first-level variables, and the strong non-linear characteristics of the mapping between first-level variables and damage effect, the ANFIS with self-adaptation and self-learning is constructed. The map between the three first-level variables and damage effect is established, and the interaction process of the various factors in the damage effect assessment are clear. Sensitivity analysis shows that assessment model has good stability. The result analysis and comparative analysis show that the process proposed in this paper can effectively assess the damage effect of anti-ship missiles, and all criteria data are objective and comparable.