飞机数字化装配系统中机身交点孔加工方法研究

针对传统交点孔加工方法加工精度低且存在回弹变形的问题,设计了一种满足飞机大部件数字化装配要求的机身交点孔精加工方法,根据交点孔的加工特性完成了机身定位与固持、数控加工中心定位以及加工工艺的总体设计,确定了交点孔加工程序原点的计算方法和编程原则,最后通过交点孔试切加工试验验证了加工方法的可行性。     

FPGA设计中的亚稳态问题及其预防方法研究

由于在复杂FPGA（Field Programmable Gate Array,现场可编程门阵列）设计中存在跨时钟域,通常会产生亚稳态现象.为有效地预防和解决该问题,分析FPGA设计中亚稳态的产生机理及其对数字信号处理系统的影响.根据不同的信号同步类型,针对单比特电平信号、脉冲信号和边沿信号,分别给出基于触发器级联的跨时钟域信号同步方法;针对并行信号,提出基于异步FIFO （First In First Out,先进先出队列）和握手协议的跨时钟域同步方法;并通过仿真手段分析信号同步方法的有效性及其适用范围.结果表明：这些方法能够正确有效地完成跨时钟域信号同步,预防可能出现的亚稳态问题,从而提高复杂FPGA设计的可靠性和稳定性.     

数字全息测量超高速撞击碎片云实验研究

在中国空气动力研究与发展中心(CARDC)超高速碰撞中心(HIRC)7.6 mm超高速碰撞设备的基础上，搭建纳秒级脉冲激光数字全息系统。提出滤波片和衰减片组合布置，减弱超高速碰撞等离子体自发光、提高信噪比的方法。实验获得了2.25 mm铝球弹丸以4.0 km/s的速度撞击0.5 mm厚铝板形成碎片云的全息图。采用小波变换算法对碎片云全息图进行重建，得到超高速撞击碎片云的三维结构和碎片大小。碎片云的轮廓呈椭球型，分为碎片云的前端、核心和外壳，碎片主要分布在弹丸破碎形成的碎片云核心，存在大碎片，且分布较集中，对后板的损伤也严重     

Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation symptoms, and (c) a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.     

基于一致性融合和神经网络的航空发动机气路系统故障诊断方法

以信息融合为基础,运用GRNN神经网络对航空发动机气路系统进行故障诊断,提出了一种基于一致性融合和神经网络相结合的故障诊断方法。试验结果表明,该方法能快速识别航空发动机气路系统故障,并且对其他机械设备的故障诊断具有一定的参考价值。     

飞机装配质量数字化检测技术研究及应用

针对飞机装配过程质量评价对数字化测量技术的需求,开展了面向飞机装配的数字化测量特征设计、测量方案设计、多系统异构测量场构建、测量误差分析与修正等技术研究,并以表面类、内部结构特征、大部件对接和活动部件装配质量的控制为例,阐述了测量设备选型、整体测量场的构建方法及其应用效果.     

一种兼容GPS和BD系统的跟踪环路相干积分方法

在城市、峡谷等复杂环境下,卫星导航信号衰减严重,接收机导航定位性能变差,甚至不能工作,给国民生产生活带来诸多不便.提高接收机弱信号的跟踪能力,研究高性能的卫星导航接收机具有重要的意义和价值.在研究分析GPS、北斗D1导航电文的调制方式和相干积分方法的基础上,构建了一种改进直方图的位同步方法,该方法借鉴直方图的思想,通过设定比特跳变的统计门限上限和多组门限下限找到比特跳变边沿.在此基础上设计实现了一种长时间相干积分方法,该方法兼容GPS电文和北斗D1导航电文,可以有效地消除导航电文跳变或者NH码跳变带来的比特翻转.最后,在FPGA平台验证了该方法可以有效提高信号信噪比,以及接收机在弱信号环境下的跟踪能力.     

Nonlinear dynamic modeling of a helicopter planetary gear train for carrier plate crack fault diagnosis

Planetary gear train plays a significant role in a helicopter operation and its health is of great importance for the flight safety of the helicopter. This paper investigates the effects of a planet carrier plate crack on the dynamic characteristics of a planetary gear train, and thus finds an effec-tive method to diagnose crack fault. A dynamic model is developed to analyze the torsional vibra-tion of a planetary gear train with a cracked planet carrier plate. The model takes into consideration nonlinear factors such as the time-varying meshing stiffness, gear backlash and viscous damping. Investigation of the deformation of the cracked carrier plate under static stress is performed in order to simulate the dynamic effects of the planet carrier crack on the angular displacement of car-rier posts. Validation shows good accuracy of the developed dynamic model in predicting dynamic characteristics of a planetary gear train. Fault features extracted from predictions of the model reveal the correspondence between vibration characteristic and the conditions (length and position) of a planet carrier crack clearly.     

Simultaneous state and actuator fault estimation for satellite attitude control systems

In this paper, a new nonlinear augmented observer is proposed and applied to satellite attitude control systems. The observer can estimate system state and actuator fault simultaneously. It can enhance the performances of rapidly-varying faults estimation. Only original system matrices are adopted in the parameter design. The considered faults can be unbounded, and the proposed augmented observer can estimate a large class of faults. Systems without disturbances and the fault whose finite times derivatives are zero piecewise are initially considered, followed by a discussion of a general situation where the system is subject to disturbances and the finite times derivatives of the faults are not null but bounded. For the considered nonlinear system, convergence conditions of the observer are provided and the stability analysis is performed using Lyapunov direct method. Then a feasible algorithm is explored to compute the observer parameters using linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed approach is illustrated by considering an example of a closed-loop satellite attitude control system. The simulation results show satisfactory perfor-mance in estimating states and actuator faults. It also shows that multiple faults can be estimated successfully.     

基于综合模糊聚类算法的液体火箭发动机故障诊断

基于液体火箭发动机正常及故障状况数据的完备程度和数据质量的不断提高,提出一种基于数据驱动的综合模糊聚类算法用于故障诊断。采用模糊c均值(FCM)算法对已知正常样本数据进行聚类得到最优的聚类中心,将所得到的聚类中心作为先验样本数据用于传递闭包法最优分类结果的选择从而得到故障检测结果,该算法只需要少量的正常先验样本数据就能快速、准确的检测出故障;随后采用FCM算法进行故障分类,可以根据现有的故障数据库进行聚类得到对应的故障类型,并且可以给出故障幅值范围。模型仿真结果表明:该算法对故障的检测率可达968%,故障隔离率达到94%。某型液体火箭发动机实际试车数据结果表明:该故障诊断算法能够准确及时的检测并隔离出故障。