蜂窝状薄壁管拉伸时的收缩分析

为研究蜂窝材料拓扑结构与其整体力学性能的关系，从非平面Vertex模型的势能形式出发，结合蜂窝薄壁管拉伸时的轴对称特征，通过变分法得到了管拉伸时母线满足的控制方程，证实了边界效应是蜂窝状薄壁管受拉时产生收缩的原因，并结合控制方程的若干特解，考察了非平面Vertex模型中材料参数对管弯曲程度的影响。结果表明，非平面Vertex模型中表征夹角势强度的参数决定了材料的整体抗弯性，而距离管端最近的3层元胞是管拉伸时的主要收缩区。最后进一步探讨了蜂窝薄壁管曲率与收缩幅度之间的非线性关系，揭示了构型曲率是蜂窝材料泊松比的影响因素之一。     

基于GCF-SB视觉注意模型的红外目标检测算法

针对复杂背景、低对比度条件下的红外目标检测，提出了一种基于灰度对比度特征 相似性贝叶斯(GCF SB)模型的红外显著性目标检测算法.建立了一种灰度对比度特征(GCF)模型，该模型利用两个通道分别提取红外图像的灰度特征和对比度特征，然后通过特征融合获得初级显著图；建立了一种基于相似性的贝叶斯(SB)模型，该模型根据初级特征图分别计算目标和背景的先验概率和似然函数，然后利用贝叶斯公式获得最终显著图，进而实现红外图像的显著性目标检测.实验结果表明，所提出算法能够有效抑制复杂背景、低对比度红外图像的噪声，增强对比度，具有较高的检测精度和鲁棒性.     

基于贝叶斯可信度的直升机安全性分析

本文基于贝叶斯网络理论建立了直升机在"人—机—环境系统"的飞行安全性模型,其目的是通过网络模型分析,发现影响安全性的薄弱环节,以及通过相应的纠正措施提高直升机飞行的安全性。     

Adaptive sensitive frequency band selection for VMD to identify defective components of an axial piston pump

The underlying study investigates single valued neutrosophic entropy based adaptive sensitive frequency band selection for variational mode decomposition(VMD) for the purpose of identifying defective components in an axial pump. The proposed methodology is applied in the following steps. First, VMD is applied for decomposing vibration signals into various frequency bands, called as modes. After computing energy of each VMD, the lower(minimum) and upper(maximum) bounds from these energy readings ...     

Joint parameter and state estimation for stochastic uncertain system with multivariate skew t noises

Due to the pulse interference, measurement outliers and artificial modeling errors, the multivariate skew t noise widely exists in the real environment. However, to date, little attention has been paid to the state estimation for systems in which the process noise and the measurement noise are both modeled as the heavy-tailed and skew non-Gaussian noise. In this paper, the multivariate skew t distribution is utilized to model the heavy-tailed and skew non-Gaussian noise. Then a probabilistic gra...     

Variational Bayesian labeled multi-Bernoulli filter with unknown sensor noise statistics

It is difficult to build accurate model for measurement noise covariance in complex back-grounds. For the scenarios of unknown sensor noise variances, an adaptive multi-target tracking algorithm based on labeled random finite set and variational Bayesian (VB) approximation is pro-posed. The variational approximation technique is introduced to the labeled multi-Bernoulli (LMB) filter to jointly estimate the states of targets and sensor noise variances. Simulation results show that the proposed method can give unbiased estimation of cardinality and has better performance than the VB probability hypothesis density (VB-PHD) filter and the VB cardinality balanced multi-target multi-Bernoulli (VB-CBMeMBer) filter in harsh situations. The simulations also confirm the robustness of the proposed method against the time-varying noise variances. The computational complexity of proposed method is higher than the VB-PHD and VB-CBMeMBer in extreme cases, while the mean execution times of the three methods are close when targets are well separated.     

基于Bayes方法的飞机压力加油系统优化算法研究

对于实际的问题而言,人们对于问题的解一般会有一个初步认识,并且这种认识会在搜索过程中逐渐加深或得到修正,这符合人们认识世界的普遍规律。基于这种认识,针对给出的飞机地面压力加油系统管路模型,使用一种基于Bayes方法的优化算法。数值方针结果表明,与其它相关优化算法相比,该算法能更高效地解决飞机地面压力加油管路节流孔的优化配置问题。     

多阶段试验下Bayes序贯估计方法

讨论在多阶段试验下正态分布参数的Bayes序贯估计，给出了估计方案，并扩充至多维的场合。对工程应用中的一些问题作了思考，提出了处置方法。     

一种密集多回波环境下的机动多目标跟踪起始算法

 本文研究密集多回波环境下的机动多目标跟踪起始问题。文中首先提出主跟踪子空间和边缘跟踪子空间的定义与性质,接着修正Bayes轨迹确定方法BTC,并将其与具有残差滤波的修正概率数据关联滤波算法MPDAF-RF有机地结合起来,提出一种适合高密集多回波环境的机动多目环跟踪起始方法——“全邻”Bayes跟踪起始算法ABTI。Monte Carlo仿真表明,本文所给出的算法不仅克服了一类概率数据关联滤波方法没有跟踪起始机理的缺陷,而且辨别目标与虚警的能力很强,不失为解决高密集多回波环境下机动多目标跟踪起始的有效方法。     

基于Bayes理论的导弹贮存可靠性试验研究

基于某导弹样本少、贮存过程需要检测、维护、故障修复等特点,利用Bayes理论推导出公式,以此公式为基础设计试验过程,进行贮存可靠性试验,收集试验数据,并且融合验前信息,最终得出调整后的失效率。