航空发动机调度方法的设计与实现

介绍了一种实现航空发动机调度方案的方法。该方法主要采用利用Ajax技术实现服务器端和客户端的数据交互,并且利用Java Script脚本在客户端生成调度图表,在减轻了服务器端负担的同时也大大改善了调度图表的显示方式。     

一种复杂系统的预测方法

提出了一种适用于复杂系统的预测方法——多因素关联预测,并以战斗机机体费用预测作为算例。     

Longitudinal behaviors of the IRI-B parameters of the equatorial electron density profiles retrieved from FORMOSAT-3/COSMIC radio occultation measurements

The electron density profiles in the bottomside F₂-layer ionosphere are described by the thickness parameter B0 and the shape parameter B1 in the International Reference Ionosphere (IRI) model. We collected the ionospheric electron density (N_e) profiles from the FORMOSAT-3/COSMIC (F3/C) radio occultation measurements from DoY (day number of year) 194, 2006 to DoY 293, 2008 to investigate the daytime behaviors of IRI-B parameters (B0 and B1) in the equatorial regions. Our fittings confirm that the IRI bottomside profile function can well describe the averaged profiles in the bottomside ionosphere. Analysis of the equatorial electron density profile datasets provides unprecedented detail of the behaviors of B0 and B1 parameters in equatorial regions at low solar activity. The longitudinal averaged B1 has values comparable with IRI-2007 while it shows little seasonal variation. In contrast, the observed B0 presents semiannual variation with maxima in solstice months and minima in equinox months, which is not reproduced by IRI-2007. Moreover, there are complicated longitudinal variations of B0 with patterns varying with seasons. Peaks are distinct in the wave-like longitudinal structure of B0 in equinox months. An outstanding feature is that a stable peak appears around 100°E in four seasons. The significant longitudinal variation of B0 provides challenges for further improving the presentations of the bottomside ionosphere in IRI.     

Fronts and thermohaline structure of the Brazil–Malvinas Confluence System

Fronts and thermohaline structure of the Brazil–Malvinas Confluence System (BMCS) are studied from climatic data, “Marathon Exp. Leg.8, 1984” data, and Sea surface temperature (SST) data base “ds277-Reynolds” (1981–2000). The South Atlantic Central Water (SACW) is divided in two main types: tropical (TW) and subtropical water (ST). Water masses, Fronts, Inter-Frontal and Frontal Zones are analysed and classified: (a) the water masses: Tropical Low-Salinity Water, Tropical Surface Water, Tropical Tropospheric Water, Subtropical Low-Salinity Water, Subtropical Surface Water, Subtropical Tropospheric Water. T,S characteristics of intermediate, deep and bottom water defined by different authors are confirmed and completed; (b) the Inter-Frontal Zones: Tropical/Brazil Current Zone, Subtropical Zone and Subantarctic Zone; (c) the Frontal Zones: Subtropical, Subantarctic and Polar, and (d) the Fronts: Subtropical Front of the Brazil Current, Principal Subtropical Front, North Subtropical Front, Subtropical Surface Front, South Subtropical Front, Subantarctic Surface Front, Subantarctic Front and Polar Front. Several stable T–S relationships are found below the friction layer and at the Fronts. The maximum gradient of the oceanographic characteristics occurs at the Brazil Current Front, which can be any of the subtropical Fronts, depending on season. Minimum mean depth of the pycnocline coincides with the Fronts of the BMCS, indicating the paths of low-salinity shelf waters into the open ocean. In the work it is shown how to recover the horizontal and vertical thermohaline structure of waters from satellite data RSMAS SST.     

应用小波神经网络进行负荷预测的MATLAB编程仿真

以咸阳地区的电力负荷数据为背景,应用小波神经网络进行短期负荷预测工作,并详细介绍了其MATLAB的编程与仿真。利用MATLAB 7.0的神经网络及小波工具箱函数进行编程仿真,不仅编程简洁,而且收敛速度快。因需要大量的训练数据进行训练,介绍了在实际编程时所用技巧。     

卫星通信水情遥测系统

阐述卫星通信自报式与呼叫式水情遥测系统的组成、功能、工作原理并简要介绍在水情遥测系统中采用海事卫星通信的优点。     

基于GRA-IPSO-SVM的航材携行需求预测研究

异地执行飞行任务中航材需求的准确预测是做好携行保障的主要内容之一,为此提出灰色关联度（GRA）与改进的粒子群算法（IPSO）及支持向量机（SVM）相结合的航材预测方法。首先运用GRA 对航材携行需求的影响因素进行分析;其次引入活性因子和非线性惯性系数改进粒子群算法,并通过IPSO 对SVM 参数进行寻优;最后使用优化后的SVM 模型预测航材需求。结果表明：GRA-IPSO-SVM 方法预测结果的均方根误差比PSO-SVM 方法下降0.16,平均绝对百分比误差下降2.18%,且预测时间减少了0.7 s。     

基于多元线性回归的发动机性能参数预测

在对发动机性能参数相关性研究基础上,结合多元线性回归预测模型,提出了一种能够考虑发动机众多因素对因变量影响的发动机性能预测模型.使用该模型对发动机排气温度(EGT)进行预测时,能够兼顾到p_4.95,N₂,T₃,N₁,p_B等性能参数对EGT影响.最后使用一组某民用机型发动机飞行试验数据对模型进行了验证,并与加权一阶局域法进行了对比.结果表明,该模型预测精度优于加权一阶局域法,该方法可以为这种机型发动机故障预测提供决策依据.      

采用超程时间建模的航空航天继电器寿命预测方法的研究

提出以电磁继电器超程时间为变量,运用时间序列回归分析和数理统计分析方法,建立航天密封继电器超程时间减小曲线寿命预测数学模型。预测和实测结果的比较,表明了该方法的有效性。     

航空发动机磨损趋势RBF变权重组合预测方法研究

航空发动机滑油中金属元素的含量受许多复杂因素的影响,单一模型预测精度相对较低,本文针对这个问题提出了RBF网络变权重组合预测模型（RBFNN-VWCF）对航空发动机零部件的磨损趋势进行研究。首先引用C-C方法确定时间序列的嵌入维数和时间延时,重构相空间确定模型的输入输出样本,然后对两种模型进行组合预测,利用k均值聚类方法确定RBF网络的中心,利用固定法确定RBF网络的宽度,采用最小二乘法确定网络的权值。结果表明,RBFNN-VWCF模型充分利用了参与组合预测的两种模型的有效信息,更客观地反映发动机零部件的磨损趋势,预测结果更为稳健、相比单一模型精度更高,具有较强的工程实用价值,为发动机下一步的维修决策提供了有力支持。