基于核偏最小二乘法的物联网无线传感网络故障分析与研究

doi:10.11959/j.issn.1000-436x.2017265

Abstract

Abstract:

With the development of intelligent and networked sensor technology,wireless sensor networks were widely used in human life and commercial fields,because wireless sensor network nodes usually only carry limited resources,it is prone to failures due to insufficient resources,the accurate and timely fault diagnosis of WSN nodes can ensure the reliability of information,thus improving the maintainability of WSN and prolonging the service life of WSN.A method of using kernel partial least squares has been proposed to predict the fault reasons,the method overcomes the defects of traditional linear regression method and the nonlinear high dimensional space for data analysis.Through many experiments,the method can absorb the characteristics of canonical correlation analysis and principal component analysis method,provide a more thorough and rich content analysi,that the reason of the fault can be predicted effectively.

Key words: wireless sensor networks, fault analysis, kernel partial least squares

CLC Number:

TP393

Guang-hai ZHOU,Zhao-long NING,Zhi-kui CHEN,Hua ZHONG,Yue-ming HU. Fault analysis and research of wireless sensor network based on kernel partial least squares[J]. Journal on Communications, 2017, 38(Z2): 94-98.

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距离	PLS			KPLS
距离	Top 1	Top 3	Top 5	Top 1	Top 3	Top 5
NC	0.094 0	0.100 7	0.091 2	0.210 0	0.131 3	0.090 0
L1	0.060 0	0.048 7	0.074 0	0.002 0	0.018 7	0.018 4
L2	0.056 0	0.048 0	0.073 2	0.002 0	0.018 7	0.018 4
KL	0.060 0	0.100 7	0.101 6	0.220 0	0.145 3	0.103 6

迭代次数	PLS			KPLS
迭代次数	Top 1	Top 3	Top 5	Top 1	Top 3	Top 5
ncomp=1	0.056 0	0.094 7	0.101 6	0.222 0	0.150 0	0.104 8
ncomp=3	0.062 0	0.096 7	0.101 6	0.224 0	0.146 7	0.103 2
ncomp=5	0.060 0	0.100 7	0.101 6	0.220 0	0.145 3	0.103 6
ncomp=10	0.060 0	0.106 7	0.101 6	0.194 0	0.135 3	0.098 0
ncomp=15	0.060 0	0.110 0	0.101 6	0.224 0	0.143 3	0.104 4

Fault analysis and research of wireless sensor network based on kernel partial least squares

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