Fiber Grating Sensor Temperature Prediction Based on Relevance Vector Machine

被引：1

作者：

Liu Fang ^{[1
]}

Yu Lei ^{[1
]}

Li Yan ^{[1
]}

机构：

[1] Wuhan Univ Technol, Sch Comp Sci & Technol, Wuhan 430070, Peoples R China

来源：

MANUFACTURING SCIENCE AND MATERIALS ENGINEERING, PTS 1 AND 2 | 2012年 / 443-444卷

关键词：

Fiber grating sensor; relevance vector machine; temperature prediction;

D O I：

10.4028/www.scientific.net/AMR.443-444.40

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Fiber grating sensor network plays an important role in evaluating the bridge health condition and gaining bridge structure characteristic. Bridge structural distortion and variation of stress is associated with temperature. So it is essential to make temperature prediction bases on the length of wave which gained from fiber grating sensor network system. Traditionally, we apply least square method to predict temperature. In this paper,we use method of relevance vector machine(RVM) to make it.

引用

页码：40 / 44

页数：5

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