基于BP神经网络的导弹保障人员可靠性分析

文章分析了导弹武器系统的保障可靠性,选取了影响保障人员可靠性的 5个因素作为输入,建立了导弹保障可靠性的神经网络模型；运用 BP算法训练数据,得出各影响因素的重要度排序；并针对提高导弹保障人员可靠 性提出了一系列解决措施。     

基于叶端定时的转子叶片裂纹监测与诊断

为了实现转子叶片裂纹非接触式监测，提出基于??0范数的叶端定时欠采样信号稀疏重构算法。针对叶端定时信号欠采样问题，建立欠采样信号稀疏表示模型，利用分块正交匹配追踪算法对叶端定时欠采样信号进行分段重构，进而监测在变转速非稳态工况下转子叶片动频的变化情况，据此判断转子叶片是否产生裂纹。针对应变片信号间隔采样的特点，研究基于同步提取变换的时频分析方法，以提高时频图的时频聚集性。开展旋转叶片裂纹扩展试验，同时采用叶端定时和应变片系统测量叶片振动。对比叶端定时和应变片的分析结果，二者均可在裂纹叶片断裂之前至少20min，监测到裂纹叶片和正常叶片的动频发生分离的现象，即裂纹萌生致使叶片动频发生偏移，表明所提出的叶端定时欠采样信号重构方法能够实现转子叶片裂纹的监测与诊断。     

基于动力学模型的旋翼动平衡故障仿真及诊断

旋翼桨叶质量不平衡造成旋翼动不平衡,从而引起直升机振动。针对旋翼动不平衡故障,建立直升机动力学模型,对桨叶质量不平衡进行故障仿真及分析,建立质量不平衡故障与调整配重的对应关系；进而提出一种 BP神经网络和遗传算法结合的旋翼调整方法,建立输入参数与桨叶配重之间的模型,将四片桨叶的挥舞角和机体横滚、俯仰 2个方向的加速度值及相位作为网络输入,通过学习训练,根据输入数据预测调整配重,从而减小直升机 振动,解决旋翼动不平衡问题。     

Non-synchronous blade vibration analysis of a transonic fan

This study numerically investigates the aeromechanic behavior of a transonic fan model with a flat tip-leading-edge on the NASA rotor 67 test case. Single-passage unsteady calculations at a near stall operating point of 82% design speed show that the dominant frequencies of mass flow were not the harmonics of the rotor rotational frequency. A full-annulus fluid–structure interaction analysis was subsequently carried out to examine the unsteady flows and their interactions with blade vibrations. The results show that the modal displacement of the backward traveling seventh nodal diameter of the second torsion mode grew exponentially, which reveals that the blade vibration was non-synchronous. The vibration pattern indicates that the aerodynamic mode was resonant with the structural vibration mode. Around the rotor tip, the circumferential vortical propagation induced by interactions among the main flow, tip leakage flow, and tip clearance vortex was the source of aerodynamic excitation. To clarify the mechanism of the non-synchronous vibration, the coupling between aerodynamic disturbance and structural response, i.e., aliasing, was summarized. The frequency spectra of the fluctuating pressure show that an aerodynamic Backward Traveling Wave (BTW) was co-aliased to a structural BTW due to the propagation of the circumferential vortex. The correlation between the frequency and free convective speed of the aerodynamic disturbance determined the directions of aliasing.     

Guided wave propagation analysis in stiffened panel using time-domain spectral finite element method

Stiffened panels have been widely utilized in fuselages and wings as critical load-bearing components. These structures are prone to be damaged under long-term and extreme loads, and their health monitoring has been a common concern. The guided wave-based monitoring method is regarded as an efficient approach to detect the damage in stiffened plates because of its wide monitoring range and high sensitivity to micro-damage. Efficient simulation of wave propagation can theoretically demonstrate the detection mechanism of the method. In this study, a Time-Domain Spectral Finite Element Method (TD-SFEM) is adopted to study the wavefield in stiffened plates, where continuous Absorbing Layers with Increasing Damping (ALID) strategy is proposed to circumvent the disturbance of reflected waves on boundaries. After the convergence analysis, the developed TD-SFEM with ALID is validated by the finite element method first. Then, wave scattering and the influence of the stiffener are investigated in detail by comparing the results with the non-stiffened structure. Finally, the effects of the parameters of the stiffener, such as the height and width, on wave propagation are studied, respectively. The results illustrate that the proposed TD-SFEM with ALID is an efficient approach to study the wave propagation in the stiffened plate and can reveal the mechanism of influence of the stiffener. It is found that the height of the stiffener changes the interference of wavefield in the plate, while the effects of the width are mainly in wave scattering and mode conversion.     

基于亲和传播算法的车辆自组织网络分簇组网方法

随着5G通信和自动驾驶汽车的发展，车辆自组织网络VANET（Vehicular Ad Hoc Network）作为一种新型的移动自组织网络，因其在改善道路安全、为驾驶员和乘客提供便利方面的潜力，而引起学术界和工业界的广泛关注。它可以通过提供交通流量、事故通知、危险警告、可能存在的定位偏差、天气等信息来增强道路安全，从而提高交通效率。由于车辆的高速移动会经常引起网络拓扑中断，因此一个设计良好的路由协议至关重要。提出了一种适用于车辆自组织网络环境的基于分簇的路由协议，设计并实现了一种基于亲和传播算法的分簇组网模型V-APC（VANET-Affinity Propagation Clustering）。通过重新定义亲和传播算法的相似函数，设计了簇头的选择过程、簇的形成过程还有簇的维护过程。结果表明：采用上述方法形成的簇，在簇内的通信性能和簇稳定性方面具有显著优势，使得该协议在路由延迟和数据包转发成功率方面表现优异。     

客机隔热隔声棉点火特性与产烟毒性研究

为研究客机隔热隔声棉点火特性与产烟毒性,使用相关装置进行了试验研究.结果表明:点火持续时间和辐射板温度均对隔热隔声棉点火具有明显促进作用.点火持续时间越长,火焰沿Y轴蔓延距离越大,点火15s时,明火附近区域的隔热隔声棉出现被烧穿现象,但烧穿面积不大.火焰沿Y轴蔓延距离增长速率却随点火持续时间的增大而减小,验证了隔热隔声...     

Macro-phenomenological high-strain-rate elastic fracture model for ice-impact simulations

The ice impact can cause a severe damage to an aircraft’s exposed structure, thus, requiring its prevention. The numerical simulation represents an effective method to overcome this challenge. The establishment of the ice material model is critical. However, ice is not a common structural material and exhibits an extremely complex material behavior. The material models of ice reported so far are not able to accurately simulate the ice behavior at high strain rates. This study proposes a novel high-precision macro-phenomenological elastic fracture model based on the brittle behavior of ice at high strain rates. The developed model has been compared with five reported models by using the smoothed particle hydrodynamics method so as to simulate the ice-impact process with respect to the impact speeds and ice shapes. The important metrics and phenomena (impact force history, deformation and fragmentation of the ice projectile and deflection of the target) were compared with the experimental data reported in the literature. The findings obtained from the developed model are observed to be most consistent with the experimental data, which demonstrates that the model represents the basic physics and phenomena governing the ice impact at high strain rates. The developed model includes a relatively fewer number of material parameters. Further, the used parameters have a clear physical meaning and can be directly obtained through experiments. Moreover, no adjustment of any material parameter is needed, and the consumption duration is also acceptable. These advantages indicate that the developed model is suitable for simulating the ice-impact process and can be applied for the anti-ice impact design in aviation.     

Adjoint-based robust optimization design of laminar flow wing under flight condition uncertainties

It is an inherent uncertainty problem that the application of laminar flow technology to the wing of large passenger aircraft is affected by flight conditions. In order to seek a more robust natural laminar flow control effect, it is necessary to develop an effective optimization design method. Meanwhile, attention must be given to the impact of crossflow(CF) instability brought on by the sweep angle. This paper constructs a robust optimization design framework based on discrete adjoint methods ...     

Orbital error propagation considering atmospheric density uncertainty

Due to the influence of various errors, the orbital uncertainty propagation of artificial celestial objects while orbit prediction is required, especially in some applications such as conjunction analysis. In the orbital error propagation of artificial celestial objects in low Earth orbits (LEOs), atmospheric density uncertainty is one of the important factors that require special attention. In this paper, on the basis of considering the uncertainties of position and velocity, the atmospheric density uncertainty is also taken into account to further investigate the orbital error propagation of artificial celestial objects in LEOs. Artificial intelligence algorithms are introduced, the MC Dropout neural network and the heteroscedastic loss function are used to realize the correction of the empirical atmospheric density model, as well as to provide the quantification of model uncertainty and input uncertainty for the corrected atmospheric densities. It is shown that the neural network we built achieves good results in atmospheric density correction, and the uncertainty quantization obtained from the neural network is also reasonable. Moreover, using the Gaussian mixture model - unscented transform (GMM-UT) method, the atmospheric density uncertainty is taken into account in the orbital uncertainty propagation, by adding a sampled random term to the corrected atmospheric density when calculating atmospheric density. The feasibility of the GMM-UT method considering atmospheric density uncertainty is proved by the further comparison of abundant sampling points and GMM-UT results (with and without considering atmospheric density uncertainty).