Framework and development of data-driven physics based model with application in dimensional accuracy prediction in pocket milling

In the manufacturing of thin wall components for aerospace industry, apart from the side wall contour error, the Remaining Bottom Thickness Error (RBTE) for the thin-wall pocket component (e.g. rocket shell) is of the same importance but overlooked in current research. If the RBTE reduces by 30%, the weight reduction of the entire component will reach up to tens of kilograms while improving the dynamic balance performance of the large component. Current RBTE control requires the off-process measurement of limited discrete points on the component bottom to provide the reference value for compensation. This leads to incompleteness in the remaining bottom thickness control and redundant measurement in manufacturing. In this paper, the framework of data-driven physics based model is proposed and developed for the real-time prediction of critical quality for large components, which enables accurate prediction and compensation of RBTE value for the thin wall components. The physics based model considers the primary root cause, in terms of tool deflection and clamping stiffness induced Axial Material Removal Thickness (AMRT) variation, for the RBTE formation. And to incorporate the dynamic and inherent coupling of the complicated manufacturing system, the multi-feature fusion and machine learning algorithm, i.e. kernel Principal Component Analysis (kPCA) and kernel Support Vector Regression (kSVR), are incorporated with the physics based model. Therefore, the proposed data-driven physics based model combines both process mechanism and the system disturbance to achieve better prediction accuracy. The final verification experiment is implemented to validate the effectiveness of the proposed method for dimensional accuracy prediction in pocket milling, and the prediction accuracy of AMRT achieves 0.014 mm and 0.019 mm for straight and corner milling, respectively.     

一种新的星载自动识别系统检测概率计算方法

针对现有星载AIS检测概率计算方法没有考虑不同解调算法对检测结果影响的问题,提出了一种基于泊松分布船舶检测模型的星载AIS检测概率计算方法。该方法首先计算混叠信号功率差和频差的联合概率分布,以及算法的解调概率,进而将两者相结合得到表征算法能力的关键参数,代入AIS检测概率模型进行计算,可使得原有模型具有适应不同解调算法的能力。仿真表明该方法可有效应用于实际工程的评估,对星载AIS的系统设计有重要的参考价值。     

基于工业机器人的飞机柔性装配技术

研究了基于工业机器人的飞机柔性装配技术,着重讨论了机器人精度补偿、末端执行器设计、法线检测与找正、系统控制、离线编程等关键技术。通过在小翼部件加工中的应用,达到了孔位精度±0.5mm、法向精度±0.5°等关键技术指标。结果表明,对于特定应用对象采用机器人技术进行飞机部件自动装配为一个理想、低成本的解决方案,随着当今工业机器人性能不断增强,配以末端执行器和相关的补偿系统,在航空工业作为装配平台是可行的。     

基于Kohonen网络的动目标实时定位融合算法

为完成对动目标的实时定位测量,有效减小测控装备组网测量实时跟踪定位误差,在建立多定位子系统组网混合式融合结构模型的基础上,利用Kohonen网络的自组织特征映射模型特点,确定各组交会数据的权值,并将其输入1个Kohonen网络进行在线竞争、融合求得目标的位置信息,增强了目标实时位置信息的连续性、完整性,减小了实时定位误差。     

Rapid design and optimization of low-thrust rendezvous/interception trajectory for asteroid deflection missions

Asteroid deflection techniques are essential in order to protect the Earth from catastrophic impacts by hazardous asteroids. Rapid design and optimization of low-thrust rendezvous/interception trajectories is considered as one of the key technologies to successfully deflect potentially hazardous asteroids. In this paper, we address a general framework for the rapid design and optimization of low-thrust rendezvous/interception trajectories for future asteroid deflection missions. The design and optimization process includes three closely associated steps. Firstly, shape-based approaches and genetic algorithm (GA) are adopted to perform preliminary design, which provides a reasonable initial guess for subsequent accurate optimization. Secondly, Radau pseudospectral method is utilized to transcribe the low-thrust trajectory optimization problem into a discrete nonlinear programming (NLP) problem. Finally, sequential quadratic programming (SQP) is used to efficiently solve the nonlinear programming problem and obtain the optimal low-thrust rendezvous/interception trajectories. The rapid design and optimization algorithms developed in this paper are validated by three simulation cases with different performance indexes and boundary constraints.     

部分可观测信息条件下装备剩余寿命预测

 针对部分可观测信息条件下退化系统的剩余寿命(RUL)预测问题,综合利用装备的历史寿命信息和性能退化信息,采用隐马尔可夫模型(HMM)对系统进行状态评估,得到系统的转移概率矩阵和观测概率矩阵;采用Bayes方法不断更新系统状态空间的条件概率分布;利用比例故障率模型(PHM)对系统进行可靠性分析,得到系统的故障率和可靠度函数,进而得到装备的剩余寿命分布。研究表明,该方法可较准确地预测装备的剩余寿命,为保障人员提供科学的维修决策依据。     

环境减灾卫星国际服务模式探索与成效

环境与灾害监测预报小卫星星座是我国对地观测系统的重要组成部分。2008年9月6日,我国成功发射环境与灾害监测预报小卫星星座A、B两颗光学小卫星（简称“环境减灾-1A、1B卫星”）。环境减灾-1A、1B卫星成功发射以来,民政部国家减灾中心（民政部卫星减灾应用中心）积极组织开展卫星在轨测试、运行管理、减灾应用、用户服务与宣传推广等工作。目前,卫星运行状态良好,各项指标正常。一年来,在成功应对国内数十场新发灾害监测与评估,积极开展国内应用服务的同时,也积极探索国际服务模式,拓展为国外救灾工作提供灾害监测产品服务,并先后成功应对澳大利亚森林大火、加拿大火灾、中缅边境火灾、海地特大地震等灾害应急监测与评估工作,在国际上获得好评,展示了我国空间技术在减灾救灾工作中的良好应用,树立了我国和平利用空间技术的大国形象。     

LEO卫星通信系统模糊逻辑动态位置区方案

文章在基于自主定位的动态位置区方案的基础上提出了模糊逻辑动态位置区方案,通过对用户在给定时间内运动模式的判定来动态改变用户的更新半径,并仿真比较了用户在不同初始更新半径下两种方案的更新和寻呼开销,以及用户在不同模糊逻辑统计时间下的更新和寻呼开销。仿真结果表明用户在该方案下的位置管理总开销相对于普通动态位置区有了明显的降低,提高了位置管理效率。     

一种基于概率的双星无源定位算法

针对双星无源定位系统采用时差、频差对地面固定辐射源进行无源定位的问题,提出了一种基于概率的双星无源定位算法。通过公式推导,将复杂的定位方程组化简为简单的二元一次方程组。在介绍定位原理的基础上对该算法进行仿真,通过仿真,分析了定位误差与时差测量精度、频差测量精度的关系。     

RTCA协议下北斗完好性降效参数算法设计及检验

目前我国北斗导航增强系统的完好性参数设计缺少针对差分信息有效性的降效参数设计,不满足航空无线电委员会（RTCA）提出的接口协议,无法同国际其他GNSS星基增强系统相兼容。根据RTCA接口协议,针对我国卫星导航系统的完好性降效参数处理算法进行了研究,利用北斗实测数据分析了完好性降效参数对用户增强服务的影响,验证了算法的有效性。结果表明,正常情况下,北斗导航系统增强服务三维定位精度可达到113m。当用户丢失部分差分改正信息时,定位精度约144m,精度下降约274%,利用完好性降效参数对过期差分信息进行降效处理,优化定位权阵,可将定位精度提高至117m,达到正常增强服务水平。