基于类脑模型与深度神经网络的目标检测与跟踪技术研究

目标检测与跟踪技术广泛应用于交通、医疗、安保和航天等领域.目前，目标检测与跟踪技术面临目标微弱、背景复杂、目标被遮挡等挑战.同时，随着脑科学研究的不断深入，人们对人脑视觉系统的理解逐渐透彻，利用类脑计算解决复杂背景下高精度目标检测与跟踪问题成为相关领域的重要研究方向.本文结合神经工程导向的类脑模型和计算机工程导向的深度神经网络(Deep Neural Networks, DNNs)，提出多种基于类脑模型与深度神经网络的目标检测与跟踪算法，包括：基于演算侧抑制的目标检测算法，基于结构 对比度(Structure Contrast, SC)视觉注意模型的弱小目标检测算法和基于记忆机制与分层卷积特征的目标跟踪算法.实验结果表明，将类脑模型和深度神经网络应用于目标检测和跟踪领域，有利于实现复杂条件下的高精度目标检测和鲁棒性目标跟踪.     

A constitutive model coupling damage and material anisotropy for wide stress triaxiality

A constitutive model that can describe the damage evolution of anisotropic metal sheets during the complex forming processes which experience wide stress triaxiality history is essential to accurately predict the deformation and rupture behaviors of the processes. In this study, a modified Lemaitre damage criterion which couples with the anisotropic Barlat 89 yield function is established. The effects of stress triaxiality, Lode parameter and shear stress on damage accumulation are considered in the constitutive model. The model is numerically implemented and applied to fracture prediction in tensile tests with different stress triaxialities and a complex deformation process with wide stress triaxiality history. The good consistency of predictions and experiments indicates that the modified Lemaitre damage model has excellent fracture prediction ability. Finally, the accuracy of the model is analyzed and discussed.     

Application of a PCA-DBN-based surrogate model to robust aerodynamic design optimization

An efficient method employing a Principal Component Analysis (PCA)-Deep Belief Network (DBN)-based surrogate model is developed for robust aerodynamic design optimization in this study. In order to reduce the number of design variables for aerodynamic optimizations, the PCA technique is implemented to the geometric parameters obtained by parameterization method. For the purpose of predicting aerodynamic parameters, the DBN model is established with the reduced design variables as input and the aerodynamic parameters as output, and it is trained using the k-step contrastive divergence algorithm. The established PCA-DBN-based surrogate model is validated through predicting lift-to-drag ratios of a set of airfoils, and the results indicate that the PCA-DBN-based surrogate model is reliable and obtains more accurate predictions than three other surrogate models. Then the efficient optimization method is established by embedding the PCA-DBN-based surrogate model into an improved Particle Swarm Optimization (PSO) framework, and applied to the robust aerodynamic design optimizations of Natural Laminar Flow (NLF) airfoil and transonic wing. The optimization results indicate that the PCA-DBN-based surrogate model works very well as a prediction model in the robust optimization processes of both NLF airfoil and transonic wing. By employing the PCA-DBN-based surrogate model, the developed efficient method improves the optimization efficiency obviously.     

基于代理模型全局优化的自适应参数化方法

对于翼型气动隐身设计问题，设计变量的配置对设计结果影响很大，而简单地增加设计变量不能保证得到理想的结果。提出一种适用于代理模型全局优化的自适应参数化方法：利用全局敏感性分析方法——基本效应法，得到设计空间关于目标函数的敏感区域信息，并以此为根据增加设计变量；利用节点插入算法将低维样本在高维空间内进行重构，避免了重新取样的工作量。相对于传统固定设计空间维度方法，自适应参数化方法在设计空间的敏感区域扩展维度，能够更加精准地描述外形并反映目标的变化趋势。通过飞翼布局翼型的气动隐身优化算例，证实自适应参数化方法可以大幅提高优化设计质量和效率。     

Applications of structural efficiency assessment method on structural-mechanical characteristics integrated design in aero-engines

In the design process of advanced aero-engines, it is necessary to carry out an effective analysis method between structural features and mechanical characteristics for a better structural optimization. Based on the structural composition and functions of aero-engines, the concept and contents of structural efficiency can reflect the relation between structural features and mechanical characteristics. In order to achieve the integrated design of structural and mechanical characteristics, one quantitative analysis method called Structural Efficiency Assessment Method (SEAM) was put forward. The structural efficiency coefficient was obtained by synthesizing the parameters to quantitatively evaluate the aero-engine structure design level. Parameterization method to evaluate structural design quality was realized. After analyzing the structural features of an actual dual-rotor system in typical high bypass ratio turbofan engines, the mechanical characteristics and structural efficiency coefficient were calculated. Structural efficiency coefficient of high-pressure rotor (0.43) is higher than that of low-pressure rotor (0.29), which directly shows the performance of the former is better, there is room for improvement in structural design of the low-pressure rotor. Thus the direction of structural optimization was pointed out. The applications of SEAM shows that the method is operational and effective in the evaluation and improvement of structural design.     

最小数据丢失量的地月中继卫星任务调度研究

月球背面的探测器必须依靠地月中继卫星进行数据传输与通信。地月中继任务包括实时性任务和延迟容忍类任务，如数传任务。当探测器等待传输的数据量超出用户存储容量时，延迟容忍类任务会由于探测器本地存储资源不足和地月中继卫星天线资源受限而无法完成，导致任务数据丢失，所以需要设计一种合理的地月中继任务调度策略，提高地月中继卫星的资源利用率，减少数据的丢失。对地月中继卫星任务调度进行了研究，在分析地月中继卫星数传任务的特点及用户的存储限制的基础上，以最小化数据丢失量为优化目标，建立了地月中继卫星任务调度模型，并设计了一种基于离散烟花算法（DFWA）的地月中继卫星任务调度算法。仿真数据分析表明，基于离散烟花算法的地月中继卫星任务调度算法在求解结果上优于遗传算法，是一种合理、有效的调度方法。     

数值模拟方法对NASA CRM模型阻力预测的影响

在复杂工程外形的数值模拟中，网格类型、规模和分布、湍流模型、数值格式等都会不同程度影响模拟结果。如何评估这些模拟方法对模拟结果的影响，并识别对模拟结果影响较显著的因素，对于CFD的发展方向有积极的借鉴指导意义。为了综合研究不同因素对商用运输机外形阻力预测的影响，以AIAA第六届阻力预测会议外形NASA CRM为研究对象，同时考虑了网格、湍流模型、无黏通量格式和体心梯度求解方法等因素对阻力预测的影响。分析中采用枚举法和正交试验设计两种方法，并使用了基于聚类分析的定性敏感性分析方法和基于Mckay主影响分析的定量方法，识别出对阻力预测影响较大的因素，这为数值模拟方法的发展指明了方向。     

A novel surrogate modeling strategy of the mechanical properties of 3D braided composites

In this paper, a surrogate-based modeling methodology is developed and presented to predict the elastic properties of three dimensional (3D) four-directional braided composites. Using this approach, the prediction process becomes feasible with only a limited number of training points. The surrogate models constructed using Finite Element (FE) method and Diffuse Approximation, reduce the computational time and cost for preparing experimental samples. In the FE model, multiscale method is applied to couple the computations of elastic properties at microscale and mesoscale. Subsequently, a parametric study is performed to analyze the effects of the three design parameters on the elastic properties. Satisfactory results are obtained via the surrogate-based modeling predictions, which are compared with the experimental measurements. Moreover, the predictions obtained from surrogate models concur well with the FE predictions. This study orients a new direction for predicting the mechanical properties based on surrogate models which can effectively reduce the sample preparation cost and computational efforts.     

An innovative approach for integrated airline network and aircraft family optimization

The determination of optimal aerial transport networks and their associated flight frequencies is crucial for the strategic planning of airlines, as well as for carrying out market research, to establish target markets, and for aircraft and crew rostering. In addition, optimum airplane types for the selected networks are crucial to improve revenue and to provide reduced operating costs. The present study proposes an innovative approach to determine the optimal aerial transport network simultaneously with the determination of the optimum fleet for that network, composed of three types of airplanes (network and vehicle integrated design). The network profit is maximized. The passenger’s demands between the airports are determined via a gravitational model. An embedded linear programming solution is responsible for obtaining potential optimal network configurations. The optimum fleet combination is determined from a database of candidate aircraft designs via genetic algorithm. A truly realistic airplane representation is made possible thanks to accurate surrogate models for engine and aerodynamics is adopted. An accurate engine deck encompassing a compression map and an innovative engine weight calculation besides an aerodynamical artificial neural network module enable a high degree of accuracy for the mission analysis. The proposed methodology is applied to obtain the optimum network comprised of twenty main Brazilian airports and corresponding fleet.     

六自由度激励台精密高刚度铰链结构设计与试验应用

精密高刚度铰链作为六自由度并联激励平台中的关键组件,其性能高低对激励台的控制精度有直接影响。针对铰链所需满足的高刚度、高基频和无间隙等要求,文章提出了基于虎克铰结构的铰链设计方法。首先根据铰链所处的工况确定选用圆锥滚子轴承作为旋转支撑部件,并通过对轴承的配置和预紧实现无间隙振动运动的要求,从而确定了铰链结构形式。然后,利用有限元法校核了结构的刚度与基频,进而完成铰链结构方案和样机制造,并将样机集成于激励台中。最后,开展了铰链动态特性试验和激励台振动控制试验,分别获取了铰链的基频和激励台控制响应。结果表明,铰链可满足激励台工作频段内的使用要求,铰链设计合理。