无线传感器网络节点故障诊断算法研究

许红艳,郭红

doi:10.13718/j.cnki.xsxb.2016.09.021

西南师范大学学报(自然科学版)

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
	姓名不能为空！
邮箱
	邮箱不能为空！非法的邮箱地址。
手机号码
	电话不能为空！请输入有效手机号!
标题
	标题不能为空！
留言内容
	内容不能为空！
验证码
	验证码不能为空！验证码错误！

无线传感器网络节点故障诊断算法研究

许红艳,郭红. 无线传感器网络节点故障诊断算法研究[J]. 西南师范大学学报(自然科学版), 2016, 41(9). doi: 10.13718/j.cnki.xsxb.2016.09.021

引用本文:

许红艳,郭红. 无线传感器网络节点故障诊断算法研究[J]. 西南师范大学学报(自然科学版), 2016, 41(9). doi: 10.13718/j.cnki.xsxb.2016.09.021

XU Hong-yan,GUO Hong. On Fault Diagnosis Algorithm in Wireless Sensor Network Nodes[J]. Journal of Southwest China Normal University(Natural Science Edition), 2016, 41(9). doi: 10.13718/j.cnki.xsxb.2016.09.021

Citation:

XU Hong-yan,GUO Hong. On Fault Diagnosis Algorithm in Wireless Sensor Network Nodes[J]. Journal of Southwest China Normal University(Natural Science Edition), 2016, 41(9). doi: 10.13718/j.cnki.xsxb.2016.09.021

无线传感器网络节点故障诊断算法研究

许红艳,郭红

郑州澍青医学高等专科学校卫生管理系,郑州,450064

On Fault Diagnosis Algorithm in Wireless Sensor Network Nodes

XU Hong-yan,GUO Hong

摘要: 针对无线传感器网络(WSN)中传感数据缺失或偏离真实值从而降低网络运行可靠性的问题，开展了关于WSN 中各种节点故障的检测和诊断算法的研究，提出了基于 SVDD 的无线传感器网络 Outlier 检测、多尺度主元分析的 WSN 节点故障诊断算法，并进行了实验验证。实验结果表明本文方法能够有效实现对节点运行状态的监视和诊断，确保感知数据的准确性和完整性，提高网络运行的可靠性。
- 无线传感器网络、故障诊断、支持向量数据描述、多尺度主元分析、递归主元分
Abstract: The impact of the unique features of WSN and the extern factors,such as strict resource con-straints,sensor aging,harsh or atrocious environments and human destruction,will make the sensed measurements deviated from the true values or miss,thus the network reliability.In order to popularize the application of WSN,it has important values of theoretical researches and practical applications to de-velop efficient fault diagnosis algorithms in WSN nodes,which realizes the surveillance and diagnosis of nodes working condition,ensure the accuracy and integrity of the data collected from WSN,and improve the reliability of WSN.The causes and classification methods of WSN fault have been analyzed,and then the fault diagnosis methods in WSN nodes based on support vector machines (SVM)and principal compo-nent analysis(PCA)method been studied in this dissertation.Experimental results show that this research method can effectively monitor and diagnose the running state of the node,and this method ensures the ac-curacy and integrity of the data,and improves the reliability of the network operation.
- wireless sensor network、fault diagnosis、support vector data description、multi-scale principal component analysis、recursive principal component analysis .

计量

文章访问数: 597
HTML全文浏览数: 406
PDF下载数: 0
施引文献: 0

无线传感器网络节点故障诊断算法研究

许红艳,郭红

郑州澍青医学高等专科学校卫生管理系,郑州,450064

关键词:

无线传感器网络、故障诊断、支持向量数据描述、多尺度主元分析、递归主元分

摘要: 针对无线传感器网络(WSN)中传感数据缺失或偏离真实值从而降低网络运行可靠性的问题，开展了关于WSN 中各种节点故障的检测和诊断算法的研究，提出了基于 SVDD 的无线传感器网络 Outlier 检测、多尺度主元分析的 WSN 节点故障诊断算法，并进行了实验验证。实验结果表明本文方法能够有效实现对节点运行状态的监视和诊断，确保感知数据的准确性和完整性，提高网络运行的可靠性。

English Abstract

On Fault Diagnosis Algorithm in Wireless Sensor Network Nodes

郑州澍青医学高等专科学校卫生管理系,郑州,450064

Keywords:

无线传感器网络、故障诊断、支持向量数据描述、多尺度主元分析、递归主元分

Abstract: The impact of the unique features of WSN and the extern factors,such as strict resource con-straints,sensor aging,harsh or atrocious environments and human destruction,will make the sensed measurements deviated from the true values or miss,thus the network reliability.In order to popularize the application of WSN,it has important values of theoretical researches and practical applications to de-velop efficient fault diagnosis algorithms in WSN nodes,which realizes the surveillance and diagnosis of nodes working condition,ensure the accuracy and integrity of the data collected from WSN,and improve the reliability of WSN.The causes and classification methods of WSN fault have been analyzed,and then the fault diagnosis methods in WSN nodes based on support vector machines (SVM)and principal compo-nent analysis(PCA)method been studied in this dissertation.Experimental results show that this research method can effectively monitor and diagnose the running state of the node,and this method ensures the ac-curacy and integrity of the data,and improves the reliability of the network operation.