基于距离加权的无线网络传感器故障诊断算法
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摘要
随着无线传感器在环境监测、医疗、军事等领域的广泛应用,无线传感器故障检测成为重中之重。现有无线传感故障诊断基于无线传感器传感数据的时空相关性进行,当无线传感器分布密集且故障较少时,能达到很好的诊断精度。提出一种基于距离加权的算法,将邻居节点的数据加权平均后与待检测点进行比较,提高了故障诊断的精度,且能对具有正常诊断的节点状态进行扩散,减少能量消耗,延长网络寿命。
With the extensive application of wireless sensors in environmental monitoring,medical treatment and military,fault detection in wireless sensor becomes more and more important.The existing wireless sensor fault diagnosis is based on spatiotemporal correlation of wireless sensor sensing data,and when the wireless sensor is densely distributed and the number of faults is small,good diagnostic accuracy can be achieved.In this paper,a distance-weighted algorithm is proposed.The data of neighboring nodes are weighted averagely and compared with the test points for diagnosis.The diagnostic accuracy of the fault is improved,and the state of the node with normal diagnosis is diffused to reduce the energy consumption and extend network life.
With the extensive application of wireless sensors in environmental monitoring,medical treatment and military,fault detection in wireless sensor becomes more and more important.The existing wireless sensor fault diagnosis is based on spatiotemporal correlation of wireless sensor sensing data,and when the wireless sensor is densely distributed and the number of faults is small,good diagnostic accuracy can be achieved.In this paper,a distance-weighted algorithm is proposed.The data of neighboring nodes are weighted averagely and compared with the test points for diagnosis.The diagnostic accuracy of the fault is improved,and the state of the node with normal diagnosis is diffused to reduce the energy consumption and extend network life.
引文
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[14]肖勇,连春雨,朱祥和.基于故障定位集的无线传感器网络故障检测[J].计算机测量与控制,2010,18(5):971-973.
[15]陈斌,杨俊杰.基于DFD算法的无线传感器网络故障诊断系统的设计[J].上海电力学院学报,2014,30(3):269-272.
[16]阳文锐,王如松,黄锦楼,等.反距离加权插值法在污染场地评价中的应用[C].中国青年生态学工作者学术研讨会,2006:2013-2018.
[2]季赛,袁慎芳,吴键,等.基于时空特性的无线传感器网络节点故障诊断方法[J].传感器与微系统,2009,28(10):117-120.
[3]陈欢欢,黄剑,王楷,等.基于节点相似性的WSNs故障检测方法研究[J].传感器与微系统,2014,33(4):10-13.
[4]KRISHNAMACHARI B,IYENGAR S.Distributed fault-bayesian algorithms for fault-tolerant event region detection in wireless sensor networks[J].Computers IEEE Transactions,2004,53(3):241-250.
[5]孙寅秋.无线传感器网络故障诊断算法设计[D].西安:西安电子科技大学,2012.
[6]孙凌逸,黄先祥,蔡伟,等.基于神经网络的无线传感器网络数据融合算法[J].传感技术学报,2011,24(1):122-127.
[7]钮永胜,赵新民,孙金玮.采用基于神经网络的时间序列预测器的传感器故障诊断新方法[J].仪器仪表学报,1998,19(4):383-388.
[8]蒲天银,饶正婵.基于神经网络的无线传感器网络故障诊断方法[J].现代电子技术,2015(23):34-36.
[9]张成.基于聚类中值比较的WSNs故障检测算法[J].传感器与微系统,2014,33(4):135-138.
[10]张鹏,冯欣,周建国.无线传感器网络中基于空间关联性的聚类异常检测算法[J].计算机应用研究,2013,30(5):1370-1372.
[11]李平,李宏,吴敏.WSNs分布式事件区域容错算法[J].计算机工程,2009,35(14):142-144.
[12]刘艺蕾,尹长川.一种基于时空相关性的传感器网络节点故障检测方法[D].北京:北京邮电大学,2016.
[13]YAO B,CHEN Q.On the temporal-spatial correlation based fault-tolerant dynamic event region detection scheme in wireless sensor networks[J].Lecture Notes in Computer Science,2007(1):511-523.
[14]肖勇,连春雨,朱祥和.基于故障定位集的无线传感器网络故障检测[J].计算机测量与控制,2010,18(5):971-973.
[15]陈斌,杨俊杰.基于DFD算法的无线传感器网络故障诊断系统的设计[J].上海电力学院学报,2014,30(3):269-272.
[16]阳文锐,王如松,黄锦楼,等.反距离加权插值法在污染场地评价中的应用[C].中国青年生态学工作者学术研讨会,2006:2013-2018.