SINS／GPS组合系统的蒙特卡洛仿真

以考虑位置误差相关项的伪距率观测模型，对遥感中使用的SINS/GPS为距、伪距率组合系统进行了蒙特卡洛仿真。结果表明，组合系统的长期位置精度能达到5m以内；GPS数据更新率低于SINS，在GPS测量时间间隔内，组合系统的性能仅由SINS决定，虽然SINS的误差随时间积累，但在GPS测量时间间隔为秒数量级的情况下，即使采用中等精度的惯性的误差随时间积累，但在GPS测量时间间隔为秒数量级的情况下，即使采用中等精度的惯性仪表，其相对位置精度可达到厘米级（这里相对位置精度指组合系统在GPS测量时间间隔内位置误差的变化范围）。     

航天材料热物理性能测试技术的发展现状

根据航天材料热物理性能测试技术的特点 ,系统介绍了国内航天材料热物理性能测试技术的发展状况和发展趋势 ,并详细介绍了目前我国航天材料热物理性能测试领域中所具备的测试技术和测试装置、航天热物理性能所涉及的研究领域和内容以及目前正在开展的研究工作。     

测量结果的不确定度

不确定度是测量质量的重要指标。根据测量分布,提出了两类不确定度的评定方法,阐明了合成不确定度与总不确定度的计算和性质,并举出了应用例子。     

双脉冲瞬态散斑全场测量方法研究CSCD

散斑测量技术在瞬态振动过程测量中具有不可或缺的重要地位。提出双脉冲瞬态散斑全场测量技术，解决了双脉冲激光器与双曝光相机的时序同步的关键技术，设计了基于双脉冲激光器的瞬态散斑光路系统，搭建了双脉冲瞬态散斑全场测量系统，从而实现了（2~800）μs 时间间隔内连续可调的瞬时振动形貌的测量。     

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.     

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.     

基于特征的数控编程技术在航空企业的推广应用

针对国内航空企业飞机结构件数控编程中存在的重复工作量大、效率低、质量不稳定、规范性差等问题,通过面向多主机厂推广基于特征的数控编程技术,切实提高飞机结构件数控编程的效率与质量.首先概述了基于特征的快速程编(FBM NUAA)系统的整体架构,并且介绍了基于特征的数控编程技术在多家主机厂中的推广与应用情况,以及前期推广中遇到的问题,并提出了解决方案.根据多主机厂多机型过百项飞机结构件的实际应用结果表明采用基于特征的快速程编系统进行数控编程,刀轨平均自动生成率超过90％,编程时间较传统编程方式平均缩短70％以上.     

An Artificial Neural Network based approach for estimation of rain intensity from spectral moments of a Doppler Weather Radar

By using a Doppler Weather Radar (DWR) at Shriharikota (13.66°N & 80.23°E), an Artificial Neural Network (ANN) based technique is proposed to improve the accuracy of rain intensity estimation. Three spectral moments of a Doppler spectra are utilized as an input data to an ANN. Rain intensity, as measured by the tipping bucket rain gauges around the DWR station, are considered as a target values for the given inputs. Rain intensity as estimated by the developed ANN model is validated by the rain gauges measurements. With the help of a developed technique, reasonable improvement in the estimation of rain intensity is observed. By using the developed technique, root mean square error and bias are reduced in the range of 34–18% and 17–3% respectively, compared to Z–R approach.     

面向高级在轨系统的动态服务质量保证方法研究

AOS(Advanced Orbiting System,高级在轨系统)已经逐渐被各国空间组织采用,随着空间任务的发展趋势更多样化和复杂化,对AOS的QoS(Quality of Service,服务质量)也提出了更高要求.针对AOS服务质量的提升需求,提出了一种虚拟信道优先级策略,使用大容量缓存结合数据压缩动态策略和遥测数据抽帧策略相结合的QoS保证方法,通过分析返向链路带宽与航天器遥测用户带宽的裕量,可以动态调整QoS保证,以适应不同应用环境下的航天器AOS的QoS保证需求.通过模拟不同的工况进行仿真试验,结果表明,该AOS服务质量保证方法适用于返向链路带宽裕量充足和不足的工况,比传统的全同步策略和同步异步结合策略拥有更广泛的适应范围.     

智能数控机床及其技术体系框架

首先简要介绍了数控机床的发展趋势,其次结合当前学术界及工业界的实践,对智能机床的概念进行了定义,然后提出了智能机床的技术体系框架,并详细阐述了智能数控系统、智能元器件以及智能化应用技术等智能机床中的关键技术.