基于概率包络的轮对轴承故障诊断方法

信号不确定性的正确表达是故障诊断的先决条件。然而,在实际情况中,轮对轴承的信号存在各种不确定性,采用传统方法处理这类不确定性,存在信息丢失问题。提出一种基于概率包络的轮对轴承故障诊断方法。对原始信号进行分布类型检验,针对不同分布特点使用不同方法进行概率包络建模。提取概率包络模型的几何形状作为故障特征,并将其输入支持向量机(SVM)训练获得故障诊断模型。以公共数据集及实测数据进行诊断测试,并对诊断结果进行比对验证。实验结果表明,该方法合理有效,提高了诊断精度和效率。

一种改进的空间信号完好性监测算法

针对Galileo系统空间信号完好性监测方案中两项关键技术点做出改进,首先提出改进临界圆法,从坐标系转换角度解决最坏用户位置方位角转换的复杂度问题;其次引入"截尾概率包络"概念,改善原模型对非零均值空间信号误差值高斯分布的过分包络问题;最后在无故障、阶跃类故障、斜坡类故障3种模式下,对比分析改进方案前后系统的完好性性能;结果表明,完好性阈值对实时空间信号误差估计值的平均包络紧度由3.89米改善至2.62米,对斜坡类故障的告警更加及时。

On Minimizing Delay with Probabilistic Splitting of Traffic Flow in Heterogeneous Wireless Networks

In the paper,we propose a framework to investigate how to effectively perform traffic flow splitting in heterogeneous wireless networks from a queue point.The average packet delay in heterogeneous wireless networks is derived in a probabilistic manner.The basic idea can be understood via treating the integrated heterogeneous wireless networks as different coupled and parallel queuing systems.The integrated network performance can approach that of one queue with maximal the multiplexing gain.For the purpose of illustrating the effectively of our proposed model,the Cellular/WLAN interworking is exploited.To minimize the average delay,a heuristic search algorithm is used to get the optimal probability of splitting traffic flow.Further,a Markov process is applied to evaluate the performance of the proposed scheme and compare with that of selecting the best network to access in terms of packet mean delay and blocking probability.Numerical results illustrate our proposed framework is effective and the flow splitting transmission can obtain more performance gain in heterogeneous wireless networks.

非正态分布假设下的完好性阈值计算与分析

引入"概率包络"概念,从分析复杂多路径误差的概率分布入手,推导了两种非高斯分布的多路径误差概率分布模型,改进了两种基于污染正态分布的完好性阈值计算方法,并分别在伪距域和定位域对非高斯误差分布模型进行高斯概率包络分析,计算相应的均方差膨胀因子,从理论上体现了完好性阈值计算方法的严密性和有效性。仿真计算结果表明,两种改进的完好性阈值计算结果都能够对污染正态分布误差模型实现高斯概率包络,但第一种改进方法计算结果相对比较保守,第二种改进方法计算结果更加优化。