摘要
在无线传感器网络(wireless sensor network,简称WSN)中通常需要对网络节点所测量的数据进行处理来判断WSN的运行是否可靠。针对传统算法存在计算复杂、能耗大的问题,提出一种基于粒子群优化算法及高斯分布的WSN节点故障诊断方法。根据粒子群优化算法规则简单和收敛速度快等特点,对节点所测数据进行优化并得到一个相应的阈值范围,通过高斯分布判断所测数据是否满足与所定阈值范围之间的关系来判定节点是否发生故障。试验结果表明,该故障诊断方法能及时、有效地发现WSN异常并诊断出故障节点,提高了WSN工作的可靠性。
In the Wireless Sensor Network(WSN),the operation reliability is usually evaluated by processing the measured data at network nodes.As there are the problems of the complex calculation and large energy consumption in the traditional algorithms,a method for fault diagnosis of nodes in WSN based on particle swarm optimization and Gaussian distribution is proposed in this paper.Because of the characteristics of simple rules and fast convergence rate of PSO,the tested data are optimized and a corresponding threshold level is obtained.Then determine whether the node is good through judging whether the tested data meet the relationship with the threshold value range based on Gaussian distribution.The experimental results show that this fault diagnosis method can find the fault nodes promptly and effectively and improve the reliability of WSN greatly.
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2013年第1期149-152,172,共4页
Journal of Vibration,Measurement & Diagnosis
基金
重庆市科技攻关基金资助项目(CSTC2011AC2179)
重庆市经济与信息化委员会基金资助项目(渝经信科技[2010]9号)
重庆市九龙坡区科委资助项目(九龙坡科委发[2009]52
53号)
关键词
无线传感器网络
故障诊断
粒子群优化算法
高斯分布
wireless sensor network(WSN),fault diagnosis,particle swarm optimization(PSO),Gaussian distribution
