空间机器人一体化仿真系统的研究与实现

为对空间机器人关键算法进行验证和评估,开发了一套一体化仿真系统。该系统基于模块化设计思想,由遥测遥控接口、轨迹规划与控制、系统动力学模型、系统3D几何模型、相机成像模型、图像处理与位姿测量、碰撞检测与安全预警等模块组成。其中,3D实体模型及仿真场景由OSG(Open Scene Graph)建立,各关键模块的算法采用C语言编程实现,可对空间机器人执行在轨任务的关键算法进行闭环验证。最后对两种典型工况进行了仿真实验,结果表明了该系统的有效性。     

一种多代路径通量分析化学机理简化方法

基于路径通量分析,在考虑组分间直接和间接多代相关反应的基础上,建立了一种新型化学机理简化方法。以预选组分为基础,通过计算预选组分直接参与,以及第二代、第三代和第四代间接参与的所有生成反应与消耗反应中其它组分相对于预选组分的路径通量之和,以此决定相关组分及其所参与反应的取舍。用该多代路径通量分析简化法对甲烷及正庚烷反应机理进行了简化,计算结果与详细化学机理、直接关系图简化法简化结果、二代路径通量分析简化法简化结果进行了对比,结果证明了该多代路径通量分析简化法具有更高的简化精度。多代路径通量分析简化法为反应流模拟中大型化学机理的精确简化提供了一种新的解决思路。     

Multipath Separation-Direction of Arrival (MS-DOA) with Genetic Search Algorithm for HF channels

Direction-of-Arrival (DOA) defines the estimation of arrival angles of an electromagnetic wave impinging on a set of sensors. For dispersive and time-varying HF channels, where the propagating wave also suffers from the multipath phenomena, estimation of DOA is a very challenging problem. Multipath Separation-Direction of Arrival (MS-DOA), that is developed to estimate both the arrival angles in elevation and azimuth and the incoming signals at the output of the reference antenna with very high accuracy, proves itself as a strong alternative in DOA estimation for HF channels. In MS-DOA, a linear system of equations is formed using the coefficients of the basis vector for the array output vector, the incoming signal vector and the array manifold. The angles of arrival in elevation and azimuth are obtained as the maximizers of the sum of the magnitude squares of the projection of the signal coefficients on the column space of the array manifold. In this study, alternative Genetic Search Algorithms (GA) for the maximizers of the projection sum are investigated using simulated and experimental ionospheric channel data. It is observed that GA combined with MS-DOA is a powerful alternative in online DOA estimation and can be further developed according to the channel characteristics of a specific HF link.     

编队卫星防碰撞规避路径规划方法与控制研究

针对编队卫星在构型重构和构型失效重组时发生碰撞可能性最大的两种机动工况,采用数学规划的方法对其进行防碰撞规避准则、规避策略和控制方面的研究;并通过系统可控性证明出无径向推力相对于全向推力,也可以达到目标相位点只是燃料消耗得多。对编队构型失效重组工况中备份星机动前停泊位置,进入编队位置选择和启动时刻选择以及故障星离开编队后,目标轨道确定等问题通过数学仿真的形式予以解答。仿真结果表明,该研究方法真实可信、简便有效。     

基于遗传算法的航空发动机管路优化设计

本文根据航空发动机管路的结构和振动特点 ,以有限元计算为基础 ,采用遗传算法为优化方法 ,在通用有限元软件 NASTRAN的平台上开发了管路振动设计优化程序。本文以调频和调幅为目标函数 ,对某一真实导管进行了优化设计 ,计算和分析表明 ,本方法能快速高效地获得最优解 ,应力计算证明这些解满足工程要求的应力分布 ,并建议在必要情况下增加管路用金属橡胶减振器以降低可能出现的振动过大。     

基于遗传算法的测站资源优化分配方法研究

针对测站级测控资源分配中存在的测控任务冲突问题,根据资源分配的一般原则及最优准则,建立资源分配优化模型,利用遗传算法给出该模型的求解方法及步骤。通过实例分析,证明该方法用于解决资源分配问题行之有效。     

基于非线性Wiener过程航空发动机性能退化预测

针对线性随机过程航空发动机剩余使用寿命预测精度不高的问题,提出一种漂移系数为指数形式的非线性Wiener过程发动机性能退化建模,进而预测航空发动机的剩余寿命。基于直接监测发动机性能退化数据,构建发动机性能退化模型,根据Wiener过程首达阈值时间的数学性质,推导出剩余寿命的概率分布。通过极大似然估计构建退化模型中未知参数的似然函数,利用遗传算法得到发动机总体模型参数的离线估计值。考虑到不同发动机个体间的差异性,采用贝叶斯公式,结合发动机的实时监测数据与总体模型参数的先验分布对模型中随机参数进行实时更新,从而对个体发动机的剩余寿命实时预测。最后,选择商用航空发动机仿真数据集(C-MAPSS)进行实验,结果表明：针对个体发动机基于非线性随机过程方法,实时更新非线性Wiener方法能够提高航空发动机循环中期剩余寿命预测的准确性,提供更加可靠的预防性维修决策。     

视觉无人机棚内煤场自主飞行与地图构建

针对目前室内大型煤场煤储量估计方法中,固定位置激光打点方式存在盲区、不灵活、精度差,以及基于多旋翼无人机的方法难以适应无GPS的室内环境等缺点,提出结合视觉定位的无人机室内自主飞行盘煤方法。该方法通过融合5个方向的视觉信息,并结合无人机路径规划及避障算法,对煤堆进行了全覆盖的视觉成像,然后,通过运动推断结构方法进行三维建模,用于估计煤储量。经实验验证,所提方法有较好的室内定位精度,基于三维建模的煤堆储量估计与实际储量较为接近,证明了其有效性和可行性。     

Development cost prediction of general aviation aircraft using combined estimation technique

Obtaining accurate development cost estimation results of general aviation aircraft is crucial for companies to adopt the best strategy in the development process. To address this problem, this paper proposes a combination of three commonly used single prediction methods. The optimal weight values of the three single prediction methods are determined by utilizing the shortest ideal point method. Ten cost datasets collected from literature are utilized for fitting and testing the combined prediction method, and the weight coefficients of the three individual prediction methods are calculated as 0.6859, 0.0035 and 0.3106, respectively. The results of this study indicate that the developed method has better fitting and estimation accuracy than that of the three individual methods, with average fitting and predicting error values of 2.60% and 6.43%, respectively. Additionally, the cost data of military and civil aircraft development from literature are collected for verification. The results further confirm that the proposed method is not only superior to the single prediction methods in terms of high precision but has wider applications. More importantly, this research can provide important reference for general aviation aircraft companies in term of product cost planning and corporate sales strategies.     

An intelligent target detection method of UAV swarms based on improved KM algorithm

Complete and efficient detection of unknown targets is the most popular application of UAV swarms. Under most situations, targets have directional characteristics so that they can only be successfully detected within specific angles. In such cases, how to coordinate UAVs and allocate optimal paths for them to efficiently detect all the targets is the primary issue to be solved. In this paper, an intelligent target detection method is proposed for UAV swarms to achieve real-time detection requirements. First, a target-feature-information-based disintegration method is built up to divide the search space into a set of cubes. Theoretically, when the cubes are traversed, all the targets can be detected. Then, a Kuhn-Munkres (KM)-algorithm-based path planning method is proposed for UAVs to traverse the cubes. Finally, to further improve search efficiency, a 3D real-time probability map is established over the search space which estimates the possibility of detecting new targets at each point. This map is adopted to modify the weights in KM algorithm, thereby optimizing the UAVs’ paths during the search process. Simulation results show that with the proposed method, all targets, with detection angle limitations, can be found by UAVs. Moreover, by implementing the 3D probability map, the search efficiency is improved by 23.4%–78.1%.