Remaining useful life prediction based on variation coefficient consistency test of a Wiener process

High-cost equipment is often reused after maintenance, and whether the information before the maintenance can be used for the Remaining Useful Life (RUL) prediction after the maintenance is directly determined by the consistency of the degradation pattern before and after the maintenance. Aiming at this problem, an RUL prediction method based on the consistency test of a Wiener process is proposed. Firstly, the parameters of the Wiener process estimated by Maximum Likelihood Estimation (MLE) are proved to be biased, and a modified unbiased estimation method is proposed and verified by derivation and simulations. Then, the h statistic is constructed according to the reciprocal of the variation coefficient of the Wiener process, and the sampling distribution is derived. Meanwhile, a universal method for the consistency test is proposed based on the sampling distribution theorem, which is verified by simulation data and classical crack degradation data. Finally, based on the consistency test of the degradation model, a weighted fusion RUL prediction method is presented for the fuel pump of an airplane, and the validity of the presented method is verified by accurate computation results of real data, which provides a theoretical and practical guidance for engineers to predict the RUL of equipment after maintenance.     

Identification of crystal orientation for turbine blades with anisotropy materials

A novel approach to identify the crystal orientation of turbine blades with anisotropy materials is proposed. Based on enhanced mode basis, with the main advantages of its efficiency, accuracy and general applicability, the blade vibration mode of each order is linearly constructed by several specified mode shapes, which are obtained from the considered turbine blade with specified crystal orientations correspondingly. Then, a surrogate model based on Kriging method is introduced for constructing the condensed perturbed matrix of stiffness in order to improve the efficiency even further. The constructed surrogate model allows to perform the modal analysis of turbine blades with arbitrary crystal orientations in higher efficiency, due to the fact that the elements of condensed perturbed matrix of stiffness are considered in construction of the surrogate model rather than concerning the perturbation of all the elements of the initial stiffness matrix for the blade. Genetic algorithm is finally employed to optimize the defined fitness functions in order to identify the crystal orientation angles of turbine blades. Several corresponding examples demonstrated the accuracy, efficiency and general applicability of the proposed method.     

基于快速响应的导航星座重构构型设计

针对有卫星失效下的导航星座,提出发射快速响应卫星的方法来对星座的空间构型进行重构,以实现修复和改善星座性能的目的.对快速响应任务中快速响应卫星的发射方式和入轨方式进行分析,建立快速响应卫星响应时间的数学模型;建立基于快速响应的重构构型优化模型,对优化问题中的优化变量、约束条件、目标函数进行分析;以北斗中MEO卫星失效为例,利用NSGA Ⅱ算法对优化模型进行求解,并采用双层编码的方式对优化参数进行编码得到以星座性能和响应时间为目标函数下的Pareto前沿.从结果可以看出该重构方法能有效提升受损星座的性能,同时Pareto前沿中对应的所有重构策略中,响应时间均小于一天.     

全源定位与导航的统一理论框架构建

针对多导航传感器的信息融合复杂性的问题,提出了一种基于全源定位与导航的信息融合统一理论框架。该框架将目前导航领域的主要定位导航技术分成了与时间无关的定位导航技术方法以及与时间相关的定位导航技术。首先,主要从数学的角度将各种导航技术的测量模型抽象为统一的表达形式,提出了位置、姿态、速度函数的概念,讨论了各种测量方法的测量函数及其应用;其次,分析了航位、航姿、航速的推算方法;最后根据测量模型和运动模型构建了信息融合的基本方程,并讨论了基于贝叶斯估计的导航参数一般性估计方法。     

基于LSTAR的机载燃油泵多阶段退化建模

机载燃油泵的性能退化呈现出平稳—加速—平稳的非线性、多阶段模式,针对现有退化模型难以准确描述其全寿命周期性能退化的问题,以逻辑平滑转换自回归(LSTAR)模型为工具,对机载燃油泵出口压力传感器信号进行建模。首先,对转换后的压力传感器信号建立自回归(AR)模型,通过非线性检验说明建立LSTAR模型的必要性;然后,应用非线性最小二乘法完成参数估计;最后,在AIC准则最小及拟合优度最大的原则下,选择转换变量,通过残差进行模型的适应性检验与正态性检验。结果表明:基于LSTAR模型的拟合精度明显优于线性自回归模型。本文提出的方法成功解决了机载燃油泵性能退化的多阶段准确建模问题,为机载燃油泵的预测与健康管理(PHM)奠定了坚实的基础。     

导弹自动驾驶仪故障分析软件设计

为缩短导弹自动驾驶仪故障诊断时间,提高快速保障能力,根据驾驶仪工作原理和测试原理,探讨了故障分析软件在自动化测试设备上应用的可行性,建立了驾驶仪故障树和故障诊断流程,设计了导弹自动驾驶仪故障分析软件,分析了与自动化测试设备软件的兼容性。     

Solutions for Large-Scale and Low-Cost Access to Space in the Future

The objective of this study is to identify the requirements of access to space for the future, the required methodology, key technologies and international coop...     

高分七号卫星总体设计与技术创新

高分七号卫星(GF-7)是中国自主研制的首颗1∶1万比例尺立体测绘卫星, 是国家高分辨率对地观测系统重大专项的重要组成部分。卫星围绕“双线阵相机与激光测高仪主被动复合测绘”的新体制,形成了高精度内/外方位元素稳定性设计、高精度姿态稳定控制、首个X频段自适应高速率数据传输系统、星上智能星务管理系统等一系列关键技术和创新点,实现了少控制点或无控制点区域的大比例尺立体测绘能力。介绍了卫星的总体设计情况,总结了观测体制、高精度载荷、姿态控制、高速数传、智能星务等技术创新点,通过卫星在轨初步测试结果进行了评价,认为卫星能够满足1∶1万测绘任务的要求。     

基于多样性约束和离散度分层聚类的无监督视频行人重识别

视频行人重识别是一项应用非常广的计算机视觉任务。目前的视频行人重识别方法通常是基于监督学习的,该方法需要手工标记大量的数据,代价非常高且并不适用于现实场景。本文提出了一种从底向上的基于多样性约束和离散度分层聚类的无监督视频行人重识别方法。该方法首先将每个样本当作是一个不同的类,然后结合类内间离散度进行从底向上的分层聚类,类间和类内离散度都小的类别将被优先合并,同时在聚类准则中加入一项多样性约束来平衡每类中的样本数量,最后,利用线性变化的特征存储器动态更新模型。在Mars和DukeMTMC-VideoReID两个大型视频数据集上的实验结果表明,相比于目前先进的无监督视频行人重识别方法,本文方法在性能上有一定的提升。     

基于状态反馈的执行器故障容错控制

针对线性离散系统的执行器故障,提出了一种基于状态反馈的容错控制方法。该方法在应用自适应卡尔曼滤波进行系统状态和故障同步估计的基础上,通过故障信息和状态估计进行状态反馈,对闭环系统进行极点配置,从而修正执行器故障造成的系统误差,实现容错控制。最后,将该方法应用于飞行控制系统的执行器故障容错控制,仿真结果表明该方法不仅能够准确地进行故障估计,而且能够在故障情况下保证系统输出正常,具有一定的理论意义和实际工程应用价值。