基于改进人工蜂群算法的多值属性系统故障诊断策略

针对实际工程应用中常见的多值属性系统故障诊断策略问题,在传统人工蜂群算法(Artificial Bee ColonyAlgorithm,简称 ABC算法)的基础上,提出改进蜂群算法用于多值属性系统的测试序列寻优。首先,在蜂群算法中重新定义多值 D矩阵和五元组的含义;其次,引入方向信息概率矩阵,设置状态转移规则和矩阵元素更新策略;最后,采用导弹舵系统实例说明算法的实现过程和有效性。最终测试序列寻优结果表明:与传统的多值 Rollout算法相比,文中所提算法能得到较好的诊断策略结果,具有一定的应用价值。     

高空长航时飞行器机翼跨声速气动优化设计

高空长航时飞行器应具有升阻比高和俯仰力矩小的气动特性.基于遗传算法的随机性和隐含并行性,结合适用于多目标处理的Pareto方法,在低雷诺数和跨声速条件下,展开了高空长航时飞行器机翼外形的多目标、多设计点的数值优化设计.仿真计算结果表明,所设计的机翼具有较高的升阻比和较低的俯仰力矩,同时在设计马赫数附近升阻比的变化比较平稳,具有良好的综合气动性能.     

小样本条件下航空武器打击精度评价算法

针对现有航空武器打击精度评价算法评价范围比较狭小,评价结果比较粗糙的问题,利用数理统计的理论和方法对航空武器打击精度的评价算法进行了深入研究,提出可变双临界值评价算法.对于给定的精度要求,通过调整可靠度,利用随之而变的上临界值与下临界值两个指标对航空武器打击精度进行准确客观的评价.理论分析和实例计算表明算法是有效可行的.     

简化七阶CQKF及其在SINS大失准角初始对准中的应用

针对捷联惯性导航系统（SINS）大失准角初始对准的滤波过程，提出简化七阶正交容积卡尔曼滤波算法（7th-SCQKF）。根据简化容积卡尔曼滤波(CKF)理论，推导出改进的简化七阶CKF算法（7th-MSSRCKF），改进了原简化七阶CKF（7th-SSRCKF）的性能；同时，在7th-SSRCKF和7th-MSSRCKF基础上，引入正交半径准则，提出简化七阶CQKF（7th-SCQKF）算法，提高了滤波精度；并将简化七阶CQKF（7th-SCQKF）算法应用到SINS的大失准角初始对准仿真中，结果表明，7th-SCQKF比7th-MSSRCKF的滤波精度高，验证了新算法的正确性和有效性。     

基于结构模态的机翼带吊舱有限元建模方法

针对无有限元模型的颤振计算建模问题,提出了一种采用结构优化方法建立有限元模型的方法。依据标准算例的结构尺寸和材料特性建立其有限元模型,采用集中质量单元和连接杆模拟外挂吊舱结构,得到了机翼带吊舱的标准模型。计算其结构模态并作为优化目标,建立几何尺寸、质量与标准模型一致。但结构参数不一致的初始模型;然后采用敏度优化算法优化初始模型,得到机翼带吊舱的优化模型。计算结果表明,优化模型与标准模型的颤振速度和频率均较为接近。     

A multi-objective multi-memetic algorithm for network-wide conflict-free 4D flight trajectories planning

Under the demand of strategic air traffic flow management and the concept of trajectory based operations (TBO),the network-wide 4D flight trajectories planning (N4DFTP) problem has been investigated with the purpose of safely and efficiently allocating 4D trajectories (4DTs) (3D position and time) for all the flights in the whole airway network.Considering that the introduction of large-scale 4DTs inevitably increases the problem complexity,an efficient model for strategic level conflict management is developed in this paper.Specifically,a bi-objective N4DFTP problem that aims to minimize both potential conflicts and the trajectory cost is formulated.In consideration of the large-scale,high-complexity,and multi-objective characteristics of the N4DFTP problem,a multi-objective multi-memetic algorithm (MOMMA) that incorporates an evolutionary global search framework together with three problem-specific local search operators is implemented.It is capable of rapidly and effectively allocating 4DTs via rerouting,target time controlling,and flight level changing.Additionally,to balance the ability of exploitation and exploration of the algorithm,a special hybridization scheme is adopted for the integration of local and global search.Empirical studies using real air traffic data in China with different network complexities show that the pro posed MOMMA is effective to solve the N4DFTP problem.The solutions achieved are competitive for elaborate decision support under a TBO environment.     

Real-time fault detection method based on belief rule base for aircraft navigation system

Real-time and accurate fault detection is essential to enhance the aircraft navigation system’s reliability and safety. The existent detection methods based on analytical model draws back at simultaneously detecting gradual and sudden faults. On account of this reason, we propose an online detection solution based on non-analytical model. In this article, the navigation system fault detection model is established based on belief rule base (BRB), where the system measuring residual and its changing rate are used as the inputs of BRB model and the fault detection function as the output. To overcome the drawbacks of current parameter optimization algorithms for BRB and achieve online update, a parameter recursive estimation algorithm is presented for online BRB detection model based on expectation maximization (EM) algorithm. Furthermore, the proposed method is verified by navigation experiment. Experimental results show that the proposed method is able to effectively realize online parameter evaluation in navigation system fault detection model. The output of the detection model can track the fault state very well, and the faults can be diagnosed in real time and accurately. In addition, the detection ability, especially in the probability of false detection, is superior to offline optimization method, and thus the system reliability has great improvement.     

基于FDG和GA的故障诊断技术在电子对抗装备中的应用

探讨了模糊有向图（Fuzzy Directed Graph,FDG）和遗传算法（Genetic Algorithm,GA）相结合的故障诊断技术及其在电子对抗装备故障诊断中的具体应用。根据电子对抗装备组件的实际状态,应用模糊理论得出各组件发生故障的可能性,建立电子对抗装备的模糊有向图,利用遗传算法搜索出模糊有向图中可能的故障传播路径。实践表明,该技术应用在电子对抗装备的故障诊断中是行之有效的,取得了较好的诊断结果。     

IMPROVEMENT OF PHASE GRADIENT AUTOFOCUS ALGORITHM

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