基于蒙特卡罗法的航空发动机空气系统稳态算法优化

针对目前航空发动机空气系统稳态算法中收敛性依赖初值的问题,将蒙特卡罗方法与流体网络法综合应用到空气系统可压缩流体一维网络计算中,提出了一种新的计算方法Monte Carlo-Fluid Network（MC-FN）。该方法将空气系统简化为由节点和元件组成的网络,借助蒙特卡罗方法获得空气系统内各节点压力分配,再根据空气系统中各元件流阻特性和换热特性计算流量、温度。计算中通过将游动次数比较少的蒙特卡罗方法的计算结果作为流量残差法节点压力、温度的初始值,实现快速求得精确收敛解。与流量残差算法相比,MC-FN方法计算精度不变,收敛速度提升了66.5%;与线性求解法相比,MC-FN方法的计算精度提升了25.2%,收敛速度提升了43.8%。     

大数据理论在高精度惯性导航系统测试技术中的应用

当前我国高精度惯性导航系统研制已取得长足进展,但惯性导航系统的精度、可靠性和寿命等应用性能距离世界先进水平仍有差距,主要问题在于全寿命周期内的海量测试数据没有被充分挖掘、分析和应用,严重制约了惯性导航系统精度的提升、可靠性分析和寿命预估的准确性。因此,系统、准确、高效、合理地处理设计、生产、测试和使用过程中的海量数据是分析解决高精度惯性导航系统存在问题、提高生产效率、提升产品质量的有效途径。首先,详细分析了惯性导航测试系统数据采集和数据管理中存在的问题,提出大数据管理分析系统的需求和目标;其次,结合数据管理和分析中的关键技术,构建了惯性导航测试系统以数据采集层、数据支撑层和数据应用层为3大模块的大数据分析平台基本框架。为高精度惯性导航系统优化设计、提升精度、保障产品可靠性、合理预估系统寿命及适应未来战争提供了发展思路。     

Detection of aerosol pollution sources during sandstorms in Northwestern China using remote sensed and model simulated data

The present paper has used a comprehensive approach to study atmosphere pollution sources including the study of vertical distribution characteristics, the epicenters of occurrence and transport of atmospheric aerosol in North-West China under intensive dust storm registered in all cities of the region in April 2014. To achieve this goal, the remote sensing data using Moderate Resolution Imaging Spectroradiometer satellite (MODIS) as well as model-simulated data, were used, which facilitate tracking the sources, routes, and spatial extent of dust storms. The results of the study have shown strong territory pollution with aerosol during sandstorm. According to ground-based air quality monitoring stations data, concentrations of PM₁₀ and PM_2.5 exceeded 400?μg/m³ and 150?μg/m³, respectively, the ratio PM_2.5/PM₁₀ being within the range of 0.123–0.661. According to MODIS/Terra Collection 6 Level-2 aerosol products data and the Deep Blue algorithm data, the aerosol optical depth (AOD) at 550?nm in the pollution epicenter was within 0.75–1. The vertical distribution of aerosols indicates that the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) 532?nm total attenuates backscatter coefficient ranges from 0.01 to 0.0001?km^?1?×?sr^?1 with the distribution of the main types of aerosols in the troposphere of the region within 0–12.5?km, where the most severe aerosol contamination is observed in the lower troposphere (at 3–6?km). According to satellite sounding and model-simulated data, the sources of pollution are the deserted regions of Northern and Northwestern China.     

改进BA优化的MKSVDD航空发动机工作状态识别

为了提高航空发动机工作状态识别准确率和效率,避免人工识别中存在的误判和耗时耗力问题,提出了基于混沌脉冲蝙蝠算法（CRBA）优化的多核支持向量数据描述（CRBA-MKSVDD）智能识别方法。研究了多核支持向量数据描述（MKSVDD）改进策略,引入混沌脉冲发射率提高了蝙蝠算法（BA）的收敛速度和收敛精度,得到了CRBA;通过CRBA优化MKSVDD的惩罚因子和核参数,同时对飞参数据进行了特征提取;基于特征飞参数据训练了CRBA-MKSVDD分类器,并对某型发动机一个飞行架次的工作状态进行了识别。结果表明,该方法识别准确率达到97.547 9%,可用于与发动机工作状态的相关研究和应用。      

大数据在航空系统的研究现状与发展趋势

针对大数据在航空系统中的应用问题,阐述了学术界与航空工业界在航空大数据采集传输、分析技术及可视化等方面的研究现状。提出了航空大数据平台基础架构,对目前推出的几款航空大数据分析平台结合优化运营、优化维护、降低成本、降低风险等方面的需求进行了评述。指出大数据在航空系统中的应用还存在着理念、方法、技术、人等方面的挑战,并相应地提出大数据组织专门化、处理方法混合化、分析平台柔性化及跨界合作深入化等发展趋势。     

Civil unmanned aircraft system operation in national airspace: A survey from Air Navigation Service Provider perspective

Unmanned Aircraft Systems (UASs) have advanced technologically and surged exponentially over recent years. Currently, due to safety concerns, most civil operations of UAS are conducted in low-level uncontrolled area or in segregated controlled airspace. As the industry progresses, both operational and technological capabilities have matured to the point where UASs are expected to gain greater freedom of access to both controlled and uncontrolled airspace. Extensive technical and regulatory surveys have been conducted to enable the expanded operations. However, most surveys are derived from the perspective of UAS own operating mechanism and barely consider interactions of their non-segregated activities with the Air Traffic Management (ATM) system. Hence, to fill the gap, this paper presents a survey conducted from the perspective of Air Navigation Service Provider (ANSP), which serves to accommodate these new entrants to the overall national airspace while continuing flight safety and efficiency. The primary objectives of this paper are to: (A) describe what typical ANSP-supplied UAS Traffic Management (UTM) architecture is required to facilitate all types of civil UAS operations; (B) identify three major ANSP considerations on how UAS can be accommodated safely in civil airspace; (C) outline future directions and challenges related with UAS operations for the ANSP.     

Influence of leading edge with real manufacturing error on aerodynamic performance of high subsonic compressor cascades

To investigate the influence of real leading-edge manufacturing error on aerodynamic performance of high subsonic compressor blades, a family of leading-edge manufacturing error data were obtained from measured compressor cascades. Considering the limited samples, the leading-edge angle and leading-edge radius distribution forms were evaluated by Shapiro-Wilk test and quantile–quantile plot. Their statistical characteristics provided can be introduced to later related researches. The parameterization design method B-spline and Bezier are adopted to create geometry models with manufacturing error based on leading-edge angle and leading-edge radius. The influence of real manufacturing error is quantified and analyzed by self-developed non-intrusive polynomial chaos and Sobol’ indices. The mechanism of leading-edge manufacturing error on aerodynamic performance is discussed. The results show that the total pressure loss coefficient is sensitive to the leading-edge manufacturing error compared with the static pressure ratio, especially at high incidence. Specifically, manufacturing error of the leading edge will influence the local flow acceleration and subsequently cause fluctuation of the downstream flow. The aerodynamic performance is sensitive to the manufacturing error of leading-edge radius at the design and negative incidences, while it is sensitive to the manufacturing error of leading-edge angle under the operation conditions with high incidences.     

一种高光谱图像的双压缩感知模型

高光谱图像因其海量数据性,给存储、传输及后续分析处理带来了挑战。压缩感知理论提供了一种全新的信号采集框架。针对高光谱数据的三维特性,提出一种双压缩感知的采样与重构模型。该模型在采样阶段兼顾高光谱数据的空间和谱间稀疏特性,构造了能同时实现空间和谱间压缩采样的感知矩阵;重构阶段不同于传统的压缩感知重构方法直接重构高光谱数据,而是将高光谱数据分离成端元和丰度分别进行重构,然后利用重构的端元和丰度信息合成高光谱数据。实验结果表明,所提双压缩感知在低采样率下重构精度较三维压缩采样提高了10 dB以上,更为显著的是运算速度提升了3个数量级,同时该方法还便于获得端元和丰度信息。     

非均匀环境下利用单个数据集的STAP算法

对非均匀环境下利用单个数据集的机载雷达空时自适应处理(SDS-STAP)算法进行了研究。针对现有单个数据集类空时自适应算法存在的问题,提出了一种基于对待测数据集进行空时二维滑窗处理的二维幅度相位估计(2D-APES)算法。该算法利用回波的统计信息,不仅放宽了算法处理器对于雷达系统阵元数与脉冲数选取的约束,而且能够有效抑制杂波及待测单元内的干扰,同时降低了处理器的计算复杂度。最后,仿真数据及实测数据实验验证了所提算法的正确性与有效性。