多参数载荷组合的概率分布研究

本文提出了航空发动机多参数载荷谱编制的概率分布方法。首先根据发动机构件受力特点选取基准参数,然后根据多参数载荷时间历程统计出各参数之间的双参数表,利用双参数表对载荷参数进行相关性检验,获得各参数之间的相关关系以及相关参数的相关区间,进而得到拟参数,再根据实测参数载荷历程统计出拟双参数表,并求出参数的边缘概率分布和条件概率分布,最后根据概率理论求解任意参数组合下发生的联合概率。利用该方法编制了某战斗机发动机的多参数载荷谱,给出了3个方向的过载与发动机转速组合的发生概率。      

数理统计在机载设备延寿中的应用

介绍了利用数理统计分析开展机载设备寿命分布和故障水平研究的常用方法和步骤，并结合某型多功能显示器的延寿进行了应用分析。     

Influence of atmospheric turbulence on planetary transceiver laser ranging

In this paper we investigate the influence of atmospheric turbulence on the performance of the uplink of a planetary transceiver laser ranging system using a single photon detector. We numerically combine the influence of turbulence in the mean intensity profile variations, scintillation, beam-wander induced pointing errors and stochastic time-of-flight variations, using the Hufnagel–Valley turbulence profile to model the ground turbulence behavior. We map the intensity variations due to turbulence to variations in the probability distribution of the arrival time of the 1st photon in a laser pulse, which influences the range measurement error probability distribution. The turbulence models are applied to assess the influence on single-pass range accuracy and precision statistics, as well as the parameter estimation quality of a Phobos Laser Ranging (PLR) mission.     

2013年世界直升机事故统计与分析

对2013年世界直升机事故进行了统计,按直升机飞行包线的不同阶段和事故诱因进行了分类统计和分析.介绍了欧洲多国联合开展的直升机事故分析方法研究以及改善直升机安全性的技术措施,对统计、分析结果进行了总结,并针对国内现状提出了一些相关建议.     

新时效制度处理的2024铝合金塑性性能分析

对由导电率和硬度实验初步确定的２０２４铝合金新时效制度进行了拉伸试验研究，并对拉伸塑性性能试验数据进行了数理统计分析。通过实验研究和分析，证明２０２４铝合金采用新的时效制度，在塑性性能方面满足适航要求。     

材料疲劳性能数据库

论述了材料疲劳性能数据库的库结构设计及数据处理方法。     

Stochastic structural optimization using particle swarm optimization, surrogate models and Bayesian statistics

This paper focuses on a method to solve structural optimization problems using particle swarm optimization (PSO), surrogate models and Bayesian statistics. PSO is a random/stochastic search algorithm designed to find the global optimum. However, PSO needs many evaluations compared to gradient-based optimization. This means PSO increases the analysis costs of structural optimization. One of the methods to reduce computing costs in stochastic optimization is to use approximation techniques. In this work, surrogate models are used, including the response surface method (RSM) and Kriging. When surrogate models are used, there are some errors between exact values and approximated values. These errors decrease the reliability of the optimum values and discard the realistic approximation of using surrogate models. In this paper, Bayesian statistics is used to obtain more reliable results. To verify and confirm the efficiency of the proposed method using surrogate models and Bayesian statistics for stochastic structural optimization, two numerical examples are optimized, and the optimization of a hub sleeve is demonstrated as a practical problem.     

基于连通检测和区域扩展的多重聚类方法研究

针对现有聚类算法在分选过程中存在辐射源定位和脉冲划分的困难，提出了基于连通检测和区域扩展的多重聚类方法。使用网格统计的方法对脉冲列分布密度进行量化，再借鉴图像分割算法，将量化的网格矩阵划分连通区域。基于峰值检测和梯度下降的原则扩展连通区域，通过边缘检测得到最终聚类结果。仿真结果表明，该算法能保证更多的聚类脉冲列参与参数分选，提高辐射源识别率。     

基于核密度估计算法的飞机载荷谱统计技术

受到实际条件限制,现阶段的飞机载荷谱实测均采取小子样实测方法,小子样实测数据是取自真实母体的一个简单样本,很难保证数据的充分性、完整性.传统的均值统计法无法对数据缺陷进行弥补.为了克服小子样数据不足问题,将核密度估计技术用于载荷谱统计,取得了良好效果.介绍了核密度估计的相关理论基础,并以某型机下沉速度谱的统计为例,详细介绍了将核密度估计方法用于载荷谱统计的数学过程.结果显示:核密度估计方法对还原载荷谱原貌、补充小子样数据的不足问题具有良好作用.      

Improved model of ionosphere variability and study for long-term statistical characteristics

Ionospheric variability is influenced by many factors, such as solar radiation, neutral atmosphere composition, and geomagnetic disturbances. Mainly characterized by the total electron content (TEC) and electron density, the climatology of the ionosphere features temporal and spatial changes. Establishing a multivariant regression model helps substantially in better understanding the ionosphere characteristics and their long-term variability. In this paper, an improvement of the existing ionosphere multivariate linear fitting regression model is proposed and investigated using data from both the ionosonde and the global ionosphere map (GIM) derived from ground-based Global Navigation Satellite System (GNSS) observations. The proposed method gives more consideration to the impact of the solar activity and adds modeling of the annual periodic fluctuations and half-year periodic fluctuations for the F10.7 index. The improved model is verified to have a better correlation with the real observations and can help reduce the calculation uncertainty. Moreover, the proposed model is used to evaluate the fitting accuracy of the GIMs produced by five authorized data analysis centers from the International GNSS Service (IGS). The results show that there is a fixing hole in the North America region for the GIM model where the correlation between the GIM and the proposed model always returns lower values compared to other places.