摘要
针对煤矿井下巷道中无线传输延迟存在很大随机性,现有时间同步算法因无法确定延迟分布类型和参数而难以直接应用的问题,提出了一种基于被动测量的物联网时间同步信息传输延迟估计方法。在煤矿井下物联网感知层中增加一类评估节点,被动侦听感知节点间传输的时间同步信息包,获取传输延迟数据。评估节点基于极大似然估计法估计不同分布规律下的分布参数,根据Kullback-Leibler差异值确定最优分布规律;采用对数似然比确定同种分布规律下的参数突变,检测结果作为评估节点发送延迟分布规律和参数给汇聚节点的触发条件。仿真结果表明,该方法能够准确检测延迟分布规律的类型及分布参数突变。
For problems that wireless transmission delay in tunnels of coal mine underground was random greatly and current time synchronization algorithms could not be applied directly in coal mine underground because of inability to determine delay distribution and parameters,an estimation method of transmission delay of time synchronization information for Internet of things was proposed based on passive measurement.A class of evaluation node is added to perception layer of Internet of things of coal mine underground for overhearing passively time synchronization packets among perception nodes to acquire transmission delay data.Then parameters under different distribution regularities are estimated by the evaluation nodes based on the maximum likelihood estimation method and optimal distribution regularity is determined according to Kullback-Leibler difference value.Parameter mutation is detected by using loglikelihood-ratio for determining whether the evaluation nodes send delay distribution regularity and parameters to sink nodes.The simulation results show that the method detects mutation of classification of delay distribution regularity and distribution parameters accurately.
出处
《工矿自动化》
北大核心
2014年第12期37-41,共5页
Journal Of Mine Automation
基金
国家自然科学基金资助项目(51274011
61300001
51104003)
关键词
煤矿井下
物联网
时间同步
传输延迟
被动测量
参数估计
突变检测
coal mine underground
Internet of things
time synchronization
transmission delay
passive measurement
parameter estimation
mutation detection