改进电磁阀动态特性的一种方法

从建立螺管型电磁阀的数学模型入手 ,给出了不同保护回路的阀门开、关时间表达式 ,从而寻找出提高阀门动态特性的途径 ,并给出了试验验证     

油膜轴承动态特性参数及转子不平衡的统一识别

将转子不平衡作为引起转子-轴承系统振动的主要原因,本文提出了一种现场、在线识别转子系统油膜轴承动态特性参数及转子不平衡的时域方法。本方法充分利用转子的结构及模态参数以解决测点不足和激振力不可测量等问题。同传统的参数识别方法相比,本方法具有现场、在线、不需人工激振、设备简单等优点。实验结果证明了方法的可行性。     

一种典型冲击试验夹具的优化设计

根据冲击试验夹具的设计要求，以夹具几何参数为设计变量，以试件－夹具连接处的期望响应与实际响应差异最小为目标，建立了优化设计的数学模型，同时规定了几何、强度、刚度、体积等约束条件。然后在ANSYS上建立了有限元模型，采用子问题近似方法进行了动力响应优化求解，获得了合理的优化结果。本文的研究为冲击试验夹具的设计提出了一条新思路。     

航天器动力学技术的发展和挑战

本文首先简要回顾了中国航天器动力学分析设计技术的研究发展和工程应用；然后，阐述了21世纪初期中国复杂航天器的发展对航天器动力学分析设计技术提出的新要求，重点分析了在动力学分析、仿真、优化与试验方面必须突破和解决的若干关键技术；最后，对中国航天器动力学分析设计技术的发展目标和前景作了展望。     

基于频响函数的复合材料空间分布模量场识别

针对纤维编织复合材料宏观力学性能的非均匀特性,提出了基于频响函数(FRF)的复合材料梁空间分布弹性模量场的识别方法。采用基于灵敏度分析的方法构造优化问题,以实测和计算加速度频响残差范数最小为目标函数,进而通过迭代求解识别出复合材料梁弹性模量的空间分布。首先,以悬臂梁模型为研究对象进行数值仿真分析,验证识别方法的正确性。进一步开展复合材料梁模态试验研究,将复合材料三点弯曲试验获取的近似均质化弹性模量作为优化问题的初值;利用非接触测量方法获取模态试验中梁上各测点处的动位移响应,并计算得到各测点的加速度频响函数作为优化问题的输入值。结果表明:采用所提出的识别方法获取的模量场计算得到的梁上各处频响函数与试验获取值吻合,且所提方法在实测动响应存在噪声污染工况下是可行的。该方法能够为复合材料等效建模提供更加准确的弹性模量场。     

基于旋转加速度计原理的重力梯度测量技术研究与试验

旋转加速度计式重力梯度测量方法通过旋转调制的方式提取微弱的重力梯度信息。首先从测量原理出发,指出实现该方案的主要难点及对策,提炼出关键技术;其次,以多种方式开展引力梯度效应试验,验证了理论的正确性;最后,尝试了面向载体应用的动态适应性试验,达到地面低动态条件下的技术要求,为开展高动态条件下的重力梯度测量奠定基础。     

基于地月三角平动点的卫星自主定轨

近年提出了利用地月系平动点建立深空导航星座的设想。在受太阳摄动的真实力模型下,地月系平动点是不稳定的,从而会导致导航星座必须通过控制才能定点在特定区域。针对此问题,引入一种特殊的平动点轨道,即动力学替代轨道。平动点轨道卫星星座可利用星间测距数据自主定轨,由于动力学替代轨道具有长期稳定性,整个自主定轨过程不需要来自地面的测控支持,且定轨精度可达到观测精度。研究结果表明,观测资料的长短、导航卫星垂直白道面的运动分量都将影响到导航星间的自主定轨精度。该研究成果可以应用在以后的地月系导航星座中。     

Flame features and oscillation characteristics in near-blowout swirl-stabilized flames using high-speed OH-PLIF and mode decomposition methods

Flame features and dynamics are important to the explanation and prediction of a lean blowout (LBO) phenomenon. In this paper, recognition of near-LBO flame features and oscillation characterization methods were proposed based on flame spectroscopic images. High-speed planar laser-induced fluorescence measurements of OH were used to capture unique dynamic features such as the local extinction and reignition feature and entrained reactant pockets. The Zernike moment demonstrated a good performance in recognition of stability and near-LBO conditions, though the geometric moment had more advantages to characterize frequency characteristics. Low-frequency oscillations, especially at the obvious self-excited oscillation frequency around 200 Hz, were found when approaching an LBO condition, which can be expected to be used as a novel prediction characteristic parameter of the flameout limit. Proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) were used to conduct dynamic analysis of near-LBO flames. POD modes spectra showed the unique frequency characteristics of stable and near-LBO flames, which were basically in line with those at the heat-release frequency. The primary POD modes demonstrated that the radial vibration mode dominated in a stable flame, while the rotation mode was found to exist in a near-LBO flame. Analysis of modal decomposition showed that flame shedding and agminated entrained reactant pockets were responsible for generating self-excited flame oscillations.     

Real-time modular dynamic modeling for compression system of altitude ground test facilities

Modeling of a centrifugal compressor is of great significance to surge characteristics and fluid dynamics in the Altitude Ground Test Facilities (AGTF). Real-time Modular Dynamic System Greitzer (MDSG) modeling for dynamic response and simulation of the compression system is introduced. The centrifugal compressor, pipeline network, and valve are divided into pressure output type and mass flow output type for module modeling, and the two types of components alternate when the system is established. The pressure loss and thermodynamics of the system are considered. An air supply compression system of AGTF is modeled and simulated by the MDSG model. The simulation results of mass flow, pressure, and temperature are compared with the experimental results, and the error is less than 5%, which demonstrates the reliability, practicability, and universality of the MDSG model.     

Dynamic neighborhood genetic learning particle swarm optimization for high-power-density electric propulsion motor

To maximize the power density of the electric propulsion motor in aerospace application, this paper proposes a novel Dynamic Neighborhood Genetic Learning Particle Swarm Optimization (DNGL-PSO) for the motor design, which can deal with the insufficient population diversity and non-global optimal solution issues. The DNGL-PSO framework is composed of the dynamic neighborhood module and the particle update module. To improve the population diversity, the dynamic neighborhood strategy is first proposed, which combines the local neighborhood exemplar generation mechanism and the shuffling mechanism. The local neighborhood exemplar generation mechanism enlarges the search range of the algorithm in the solution space, thus obtaining high-quality exemplars. Meanwhile, when the global optimal solution cannot update its fitness value, the shuffling mechanism module is triggered to dynamically change the local neighborhood members. The roulette wheel selection operator is introduced into the shuffling mechanism to ensure that particles with larger fitness value are selected with a higher probability and remain in the local neighborhood. Then, the global learning based particle update approach is proposed, which can achieve a good balance between the expansion of the search range in the early stage and the acceleration of local convergence in the later stage. Finally, the optimization design of the electric propulsion motor is conducted to verify the effectiveness of the proposed DNGL-PSO. The simulation results show that the proposed DNGL-PSO has excellent adaptability, optimization efficiency and global optimization capability, while the optimized electric propulsion motor has a high power density of 5.207 kW/kg with the efficiency of 96.12%.