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。     

定时截尾数据回归分析方法

提出定时截尾数据回归分析方法,建立定时截尾数据回归方程,给出回归系数和标准差的最佳无偏整体估计、百分位值的点估计及其置信限估计.详细讨论了工程中常见的极值分布、Weibull分布、正态分布以及一般位置-尺度分布场合下定时截尾数据的回归分析问题.该方法可以充分利用截尾时刻的试验信息,并将各个状态下的定时截尾数据作为一个整体进行统计分析,具有信息量大、精度高的特点,从而可以在试验时间、经费等有限的情况下对产品进行高精度的寿命预测和可靠性评估.     

基于可靠性指标的测试系统校准周期优化

通过对测试系统校准周期的直接反应法(SRM)和威布尔(Weibull)可靠性模型法的分析、改进,以及对校准过程中误判率的分析测算,解决了测试系统检定决策的风险问题.首先介绍了测试系统可靠性指标的相关计量技术规范,然后通过对常用的校准周期确定方法的介绍与分析,进一步给出了测量可靠性观测值的可靠性概率函数描述方法,并利用主元分析法来综合评价不同测量参数的影响,修正了最佳校准周期的计算.通过对自动测试系统DMM(数字万用表)测量通道的检定,表明这些优化措施是可行的.      

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.      

独立多细节结构耐久性试验寿命的统计标定

在进行疲劳试验评定结构寿命时,为了能真实模拟实际结构形式和传载情况,模拟试件往往设计成多细节试件,进行不完全疲劳寿命试验,必须由多细节试件寿命推断单细节寿命.针对工程上常用的两种寿命分布形式:对数正态分布和双参数Weibull分布,以结构串联失效模型为基础,建立了由相同独立多细节结构疲劳寿命分布确定单细节寿命分布的统计标定方法.当多细节试件寿命服从对数正态分布时,可近似认为单细节寿命也服从对数正态分布,单细节寿命分布参数与多细节试件寿命分布参数间存在确定关系,并且单细节寿命数学期望和标准差均高于多细节试件相应参数;当多细节寿命服从双参数Weibull分布时,单细节寿命也服从双参数Weibull分布,其斜率不变,但位置参数按比例放大.最后给出了一个分析实例.     

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.     

数控车床故障分布的两重威布尔分段模型

为了定量地分析数控车床故障分布规律,同时也为提高其可靠性水平提供理论依据,在历时2年多收集14台数控车床故障数据的基础上,对数控车床故障率曲线的特征进行了分析,应用概率统计数学方法,建立了数控车床故障分布的两重威布尔分段模型,运用威布尔概率纸图分析法进行参数估计,据此对观测值进行了曲线拟合,拟和结果证明了分段模型的正确性.采用Laplace趋势检验法对模型进行了检验验证.从建立的两重威布尔分段模型和相应的故障率曲线上都可以区分出数控车床的早期故障期和偶然故障期,经计算早期故障期大约是5个多月,这与机床用户反映的使用初期的半年内故障频繁、故障率高相一致.该系列数控车床在使用中存在早期故障期,说明其早期故障在出厂前未被有效排除,降低了其可靠性水平.     

无失效数据下航空轴承的可靠性分析

针对某型航空轴承可靠性试验过程中出现的无失效问题,在对轴承寿命分布进行分析的基础上,首先根据多层Bayes法,研究了无失效可靠性试验中的试验分组问题,发现分组数在6~9之间选择时评估效果相对较好,且航空轴承的寿命越长分组数可以越少.其次,分析了多层Bayes法和E-Bayes法的原理和计算过程,通过Monte Carlo仿真,以最佳分组数为基础,发现两种方法的估计结果相差不大,但从可靠度角度综合来看,E-Bayes法相对较优.最后讨论了超先验分布中参数c的选值问题,通过对比分析给出了相对较适合于航空轴承无失效数据分析时的参数值.