航天装备备件配置现状SWOT分析及对策研究

全面分析航天装备备件配置现状,把握备件配置优化的主要方向,形成推动备件配置水平快速提升的关键策略,是提高航天装备备件保障科学性和高效性的重要基础。本文通过SWOT分析法对航天装备备件配置现状的优势、劣势、机遇和威胁进行了系统剖析,并在此基础上构建SWOT分析矩阵,进而基于矩阵因素的不同组合形式,研究形成改进航天装备备件配置现状、提高备件配置科学性的四种关键策略,即抓住机遇、发挥优势的S-O策略,利用机遇、克服不足的W-O策略,利用优势、应对威胁的S-T策略和弥补不足、应对威胁的W-T策略,提出当前应重点解决备件需求提报精度、库存配置科学性和协调激励机制三个现实问题,为开展航天装备备件配置问题深入研究明确了重点、确定了方向。     

Damage assessment of the target area of the island/reef under the attack of missile warhead

Under the background of vigorously developing facilities of island/reef in the world, the economic value and strategic significance of the island/reef have become increasingly important. Unfortunately, they may easily become the attacking target of missiles in the war time. Therefore, aiming at the damage quantification of the targets in the island/reef under the missile attacking, a macroscopic damage assessment model for the target area is proposed in this paper. The model focuses on the construction of the assessment model framework. Firstly, the analytic hierarchy process and the grey relational analysis are applied to measure the importance of each target in the region through four indicators of the target hazard, striking urgency, damage advantage and mission relevance, respectively. Secondly, based on the damage mechanism of shock wave and fragments to target, the corresponding damage model is established, and the damage grade of each target in the evaluated area is obtained according to the damage criteria and grading standard. Finally, the model obtains the overall damage grade of the target area by employing the fuzzy comprehensive evaluation method, with synthesizing the importance and the damage grade of each target. Through the verification of an example, it demonstrates the certain feasibility of the model and provides a certain basis and reference for the subsequent research.     

Maximizing deviation method for multiple attribute decision making under q-rung orthopair fuzzy environment

Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment, the evaluation information of alternatives given by decision makers is often fuzzy and uncertain. As a generalization of intuitionistic fuzzy set (IFSs) and Pythagoras fuzzy set (PFSs), q-rung orthopair fuzzy set (q-ROFS) is more suitable for expressing fuzzy and uncertain information. But, in actual multiple attribute decision making (MADM) problems, the weights of DMs and attributes are always completely unknown or partly known, to date, the maximizing deviation method is a good tool to deal with such issues. Thus, combine the q-ROFS and conventional maximizing deviation method, we will study the maximizing deviation method under q-ROFSs and q-RIVOFSs in this paper. Firstly, we briefly introduce the basic concept of q-rung orthopair fuzzy sets (q-ROFSs) and q-rung interval-valued orthopair fuzzy sets (q-RIVOFSs). Then, combine the maximizing deviation method with q-rung orthopair fuzzy information, we establish two new decision making models. On this basis, the proposed models are applied to MADM problems with q-rung orthopair fuzzy information. Compared with existing methods, the effectiveness and superiority of the new model are analyzed. This method can effectively solve the MADM problem whose decision information is represented by q-rung orthopair fuzzy numbers (q-ROFNs) and whose attributes are incomplete.     

Effect of nano powder (Al2O3-CaO) addition on the mechanical properties of the polymer blend matrix composite

This work describes the preparation and study of the properties of composite nanoparticles prepared by the sol-gel method which consists of two materials (Al₂O₃-CaO), and study the effect of these nanoparticles on the mechanical behavior of a polymer blend (EP 4% + 96% UPE). The powder was evaluated by X-ray diffraction analysis, scanning electron microscopy analysis (SEM), particle size analysis, and energy dispersive X-ray analysis (EDX). The mechanical behavior of the composite material was assessed by tensile test, bending test and hardness test. The evaluation results of the composite nanoparticles showed good distribution of the chemical composition between aluminum oxide and calcium oxide, smoothness in particles' size at calcination in high and low temperatures, formation of different shapes of nanoparticles and different (kappa and gamma) phases of the Al₂O₃ particles. The results of mechanical behavior tests showed marked improvement in the mechanical properties of the resulted composite material, especially at 1.5%, compared with polymer blend material without nano powder addition. The tensile properties improved about (24 and 14.9) % and bending resistance about (23.5 and 16.8) % and hardness by (25 and 22) % when adding particles of size (63.8 and 68.6) respectively. Therefore, this reflects the efficiency of the proposed method to manufacture the nanocomposite powder and the possibility of using this powder as a strengthening material for the composite materials and using these composite materials in bio applications, especially in the fabrication of artificial limbs.     

脉冲功率电源故障诊断方法研究

脉冲功率电源是电磁发射系统中最容易发生故障的薄弱环节,脉冲功率电源故障会使整个系统性能下降。针对脉冲功率电源故障,提出基于多层小波分析提取故障信息的模式搜索支持向量机故障诊断方法。通过建立脉冲功率电源的软故障模型,进行仿真分析获得电流故障数据样本,对故障样本进行离散小波分解,获得指定层细节信息的小波系数作为故障特征量;对故障特征量进行主成分分析,将小波系数进行降维,以便有效地进行故障诊断。通过实验,将所提方法故障诊断结果与其他三种故障诊断结果进行比较,验证了所提方法的有效性。     

利用最小二乘支持向量机求解潜艇内外磁场映射模型

为提高潜艇磁隐身能力,应对潜艇固定磁场进行实时监测,提出利用最小二乘支持向量机的潜艇内外磁场映射方法。结合内外映射法和最小二乘支持向量机原理,通过交叉验证优化模型参数,建立由内到外的潜艇磁场映射模型。以潜艇外部垂向固定磁场变化量为分析对象,仿真和实验结果均与标准值吻合良好。与径向基神经网络算法相比,该方法的泛化能力和推算精度有明显提高,且更符合工程实际,对闭环消磁技术的研究具有指导意义。     

面向癫痫脑电的简化深度学习模型

针对脑电信号随机性强、动态变化迅速等特点,提出了一种简化深度学习模型研究癫痫脑电识别问题。提出的模型以一维卷积神经网络为基础,在结构方面简化了卷积层、池化层等以提高模型效率,在整体框架方面应用了Keras框架,在训练优化算法方面采用RMSProp算法作为模型优化算法,通过预定义的目标函数来进行损失估计,模型设计上加入了批标准化层和全局均值池化层。基于所提模型,从三个方面研究了癫痫脑电识别问题,即:利用经验模态分解,分别选取前三阶、前五阶、前七阶、前八阶的本征模态函数分量,在简化模型上进行对比分析;利用提出模型所具备的深度学习特点,直接识别原始脑电信号而无须特征提取环节;增加了三种不同方法分别提取7类特征,对相同的脑电数据进行对比分析。性能分析结果表明:对于五类不同的脑电信号,前三阶的本征模态函数分量的识别率达到92.1%,比其他几种处理方式识别率高;前八阶的本征模态分量识别率不及原始信号,表明人工数据处理时会给数据带来噪声; 所提出的简化深度学习模型能高效处理癫痫脑电识别问题,具备较高效率和较好性能。     

飞机反区速度矢量不稳定及其控制的机理

在信号流图的基础上,提出多回路分析的方法,并用于研究反区时速度矢量不稳定及其稳定控制的机理。建立了纵向动力学的信号流图,并证明了一个回路的收敛性定理。在此基础上,通过理论分析得出了速度矢量不稳定在不同层面上的原因,也得出了速度和轨迹的发散度表达式等,并表明阻力-速度曲线、轨迹角-速度曲线、极曲线、阻力系数曲线等存在相互对应的反区和正区,并且阻力-速度曲线和轨迹角-速度曲线在斜率上成比例。研究得出进场动力补偿系统下速度矢量的稳定临界条件、收敛度、稳定机理等,理论分析和仿真比较了速度恒定进场动力补偿系统和迎角恒定进场动力补偿系统在控制性能上的差异。     

船舶静态电场跟踪的渐进更新扩展卡尔曼滤波器

为了实现利用船舶静态电场对船舶进行跟踪的目的,针对传统卡尔曼滤波算法中存在的问题,设计一种新的非线性滤波器。建立船舶的状态空间模型,分析传统卡尔曼滤波算法在船舶跟踪中存在的问题;依据渐进贝叶斯思想,利用连续白噪声与离散白噪声序列噪声协方差之间的关系,设计一种新的渐进更新扩展卡尔曼滤波器。仿真结果表明,该滤波器能有效地抑制由于初始误差较大而造成的滤波性能下降和滤波发散,能够有效地跟踪船舶,具有较高的实用价值。