欧洲返回舱CTV气动特性综述

研究分析了欧洲航天局天地往返运输系统之载人飞船返回舱CTV的气动特性，并与第一代联盟号飞船返回舱的气动特性作了对比研究。该返回舱为钝双锥外形，与联盟号飞船返回舱相比，它具有升阻比高、机动性强、稳定性好等特点。本文还对两类返回舱的气动热特性、防热材料重量、飞行弹道及通讯中断问题进行了对比分析研究。     

基于联邦滤波器的新型故障检测结构及算法

提出了一种基于联邦卡尔曼滤波器的故障检测结构,该结构利用各局部滤波器和参考滤波器共有状态之间的残差进行故障检测.并提出了2种故障检测算法:χ2检验法和Elman神经网络检验法.以组合导航系统为例进行了仿真研究,和其它算法相比该算法计算简单、可靠,不但可以快速检测出外部传感器及参考系统故障,且具有很好的容错性能,能快速检测出故障并进行隔离,使融合后系统依然保持较高精度.     

大型转动机械碰摩故障分析的声发射检测系统

汽轮发电机、空气压缩机等采用油膜支撑的大型转动机械,由于安装或运行中的原因,在转子旋转过程中,可能和器壁发生轻微的摩擦和碰击,简称碰摩.声发射技术在碰摩发生特别是故障早期诊断上有优越性.本系统的特点是没有沿用传统的计数、幅度、能量和持续时间等声发射特性参数,而是在声发射包络信号的频率分析中进行特征提取.声发射发生的过程分析和现场试验都表明这种方法对碰摩检测很敏感,在碰摩发生的起始阶段,包络谱中与转速同步的周期性分量显著增加.根据这种新的设计思想自行研制了BUAA碰摩声发射检测仪并对此作了介绍.     

应用加权中值滤波法检测薄壁梁式挠性器件下摆量

应用加权中值滤波法对薄壁梁式挠性器件下摆量进行高准确度CCD检测。薄壁梁式挠性器件在测量过程中测量图像存在高频抖动现象,因此测量准确度不高,运用加权中值滤波后使用最小二乘法细分技术,可以在实现提高测量准确度的同时,消除高频抖动带来的误差,从而可以有效提高CCD测量薄壁梁式挠性器件下摆量的准确度。实验表明,该方法比传统测量方法准确度提高20倍以上。     

Hybrid integration method for highly maneuvering radar target detection based on a Markov motion model

To detect highly maneuvering radar targets in low signal-to-noise ratio conditions, a hybrid long-time integration method is proposed, which combines Radon-Fourier Transform (RFT), Dynamic Programming (DP), and Binary Integration (BI), named RFT-DP-BI. A Markov model with unified range-velocity quantification is formulated to describe the maneuvering target’s motion. Based on this model, long-time hybrid integration is performed. Firstly, the whole integration time is divided into multiple time segments and coherent integration is performed in each segment via RFT. Secondly, non-coherent integration is performed in all segments via DP. Thirdly, 2/4 binary integration is performed to further improve the detection performance. Finally, the detection results are exported together with target range and velocity trajectories. The proposed method can perform the long-time integration of highly maneuvering targets with arbitrary forms of motion. Additionally, it has a low computational cost that is linear to the integration time. Both simulated and real radar data demonstrate that it offers good detection and estimation performances.     

双框架飞机蒙皮检测机器人切换运动控制方法

针对一种双框架飞机蒙皮检测机器人,通过分析该机器人在飞机表面上的受力情况,在飞机表面该机器人受到了非完整约束,基于牛顿-欧拉法建立了机器人非完整约束动力学模型。根据机器人机械结构和运动步态分析,将该非完整机器人系统分为子系统A和子系统B。为了实现机器人在飞机表面运动,采用反演技术和快速Terminal滑模控制相结合的思想对系统设计了控制器,提出了一种反演-滑模控制方法;对于非完整机器人子系统A和子系统B,设计了一种基于事件驱动的切换策略,实现了机器人对期望轨迹的全局渐近跟踪,并利用Lyapunov稳定性证明系统的跟踪误差收敛。仿真和试验表明,采用该切换策略和反演-滑模控制方法,双框架飞机蒙皮检测机器人可以在飞机表面自由运动并进行损伤检测,具有良好的可靠性和稳定性。     

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.     

硅半球深腔结构无损检测技术

半球深腔的加工质量是决定硅基MEMS半球陀螺精度的关键因素之一，及时检测半球深腔的形貌参数并将其反馈至加工过程，是确保高性能MEMS半球陀螺研制成功的重要措施。由于硅半球深腔的深度较大，台阶仪和光学显微成像系统无法对半球深腔的形貌特征进行有效测量。因此,需要将硅深腔结构剖开后采用扫描电镜(SEM)进行检测。这种检测方式时间周期长，且属于破坏性的样本检测，效率和测试精度都较低。提出以硅半球深腔为模具，利用PDMS铸模将硅半球深腔的结构尺寸和表面形貌转移到PDMS凸起的半球模型上，通过检测PDMS半球模型的尺寸结构和表面形貌，即可反推出硅半球深腔的尺寸特征。经实验验证，脱模后的PDMS模型可以准确地反映出半球深腔的尺寸信息，测量结果的不确定度小于5‰，有效解决了硅半球深腔无损检测的难题。     

Real-time object tracking via least squares transformation in spatial and Fourier domains for unmanned aerial vehicles

This paper addresses the problem of real-time object tracking for unmanned aerial vehicles. We consider the task of object tracking as a classification problem. Training a good classifier always needs a huge number of samples, which is always time-consuming and not suitable for realtime applications. In this paper, we transform the large-scale least-squares problem in the spatial domain to a series of small-scale least-squares problems with constraints in the Fourier domain using the correlation filter technique. Then, this problem is efficiently solved by two stages. In the first stage, a fast method based on recursive least squares is used to solve the correlation filter problem without constraints in the Fourier domain. In the second stage, a weight matrix is constructed to prune the solution attained in the first stage to approach the constraints in the spatial domain. Then, the pruned classifier is used for tracking. To evaluate proposed tracker's performance, comprehensive experiments are conducted on challenging aerial sequences in the UAV123 dataset. Experimental results demonstrate that proposed approach achieves a state-ofthe-art tracking performance in aerial sequences and operates at a mean speed of beyond 40 frames/s. For further analysis of proposed tracker's robustness, extensive experiments are also performed on recent benchmarks OTB50, OTB100, and VOT2016.