Fault detection algorithm for WSNs clustering-based medium comparison

ZHANG Cheng

doi:10.13873/j.1000-97872014.04.013

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Fault detection algorithm for WSNs clustering-based medium comparison

更新时间：2025-09-11

- Fault detection algorithm for WSNs clustering-based medium comparison
- Vol. 33, Issue 4, Pages: 135-138(2014)
- 作者机构：
  
  北京交通大学电子信息工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872014.04.013
  CLC： TN929.5;TP212.9
- Published：2014
- 稿件说明：
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[1]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(04):135-138.

ZHANG Cheng. Fault detection algorithm for WSNs clustering-based medium comparison[J]. 2014, 33(4): 135-138.
[1]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(04):135-138. DOI： 10.13873/j.1000-97872014.04.013.

ZHANG Cheng. Fault detection algorithm for WSNs clustering-based medium comparison[J]. 2014, 33(4): 135-138. DOI： 10.13873/j.1000-97872014.04.013.

摘要

无线传感器网络（WSNs）中的传感器件容易失效而导致测量数据不准确

因而

高效、实用的故障检测算法对于保证WSNs的感知质量非常重要。提出一种基于聚类中值比较（CBMC）的故障检测算法。不同于传统的中值比较的思想

该算法引入聚类方法对待检测节点的邻居节点测量数据进行分组

根据分组信息计算该节点状态。仿真实验表明:CBMC算法具有较高的故障检测率（DR）和较低的故障误检率（FPR）。

Abstract

The sensors in WSNs are prone to failure and results in inaccurate measurements

efficient and practical fault detection algorithms is very important to guarantee sensing quality of WSNs. A fault detection algorithm with clustering-based medium comparison（ CBMC） is proposed. Different from traditional medium comparison idea

CBMC introduces clustering approach to determine the status by grouping and computing the measurements of neighbor nodes. Simulation results show that the algorithm achieves a high fault detection rate（ DR） and a low false positive rate（ FPR）.

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references

分簇式无线传感器网络节点故障诊断算法研究 [J]. 刘凯,彭力. 传感器与微系统 . 2011(04)

基于加权中值的分布式传感器网络故障检测(英文) [J]. 高建良,徐勇军,李晓维. 软件学报 . 2007(05)

Spatio-temporal correlation: theory and applications for wireless sensor networks [J] . Computer Networks . 2004 (3)

Crash faults identification in wireless sensor networks [J] . Stefano Chessa,Paolo Santi. Computer Communications . 2002 (14)

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Related Institution

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