北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2007, Vol. 30 ›› Issue (4): 69-73.doi: 10.13190/jbupt.200704.69.leil

• 论文 • 上一篇    下一篇

基于Rough set理论的无线传感器网络节点故障

雷霖,代传龙,王厚军   

  1. (电子科技大学 自动化工程学院, 成都 610054)
  • 收稿日期:2006-04-21 修回日期:1900-01-01 出版日期:2007-08-30 发布日期:2007-08-30
  • 通讯作者: 雷霖

Rough Set Theory Based Fault Diagnosis of Node in Wireless Sensor Network

LEI Lin,DAI Chuan-long,WANG Hou-jun   

  1. (School of Automatic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China)
  • Received:2006-04-21 Revised:1900-01-01 Online:2007-08-30 Published:2007-08-30
  • Contact: LEI Lin

摘要:

提出了一种无线传感器网络(WSN)节点故障诊断的新方法,首先基于粗糙集理论中改进的可辨识矩阵算法得到故障诊断决策的属性约简;然后通过属性匹配的故障分类算法,建立一套WSN节点故障诊断方法,对WSN节点的各个模块分别进行具体的故障诊断和定位. 仿真实验表明,该方法在WSN节点故障诊断时通信代价小、能量消耗低、诊断准确率高,因而具有在能量有限的WSN节点中应用的可能性.

关键词: 故障诊断, 无线传感器网络, 粗糙集理论, 可辨识矩阵, 属性约简

Abstract:

For facilitating the efficient routing planning, node management for upper computers or sink nodes, longdistance node service and prolonging the lifetime of wireless sensor network (WSN), a new method for node fault diagnosis in WSN is proposed. The attribute reduction for decisionmaking of fault diagnosis is found based on the discriminate matrix in rough set theory. The algorithms of node fault classification are proposed based on attribute matching. The fault can be located and diagnosed individually for each node and module in WSN. Simulations show that the proposed method yields high diagnosis accuracy with low communication cost and energy consumption. It is suitable for wireless sensor networks with stringing energy limits.

Key words: fault diagnosis, wireless sensor network, rough set theory, discriminate matrix, attribute reduction

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