DocumentCode :
1956885
Title :
Temperature prediction with FBG sensor based on relevance vector machine
Author :
Liu, Fang ; Yu, Lei ; Li, Yan ; Qi, Quan
Author_Institution :
Nat. Eng. Lab. for Fiber Opt. Sensing Technol., Wuhan Univ. of Technol., Wuhan, China
Volume :
1
fYear :
2012
fDate :
20-21 Oct. 2012
Firstpage :
414
Lastpage :
417
Abstract :
With the wide application areas and increase industrial benefit of fiber bragg grating (FBG) sensors, the main concerns of how to build the realtime, efficient and stable monitoring system based on fiber sensing have been raised, which can provide early warning and decrease damage loss. Furthermore, the mass data include noises and uncertain information from the monitoring system. Evaluation of monitoring system dealing with noisy and uncertain data becomes the hot spot and difficulty. When FBG sensor network is employed to evaluate different structure health condition, the structural distortion and variation of stress are heavily associated with temperature, so it is essential to get higher temperature prediction accuracy using FBG sensors. Relevance vector machine is applied to regression calculation between wavelength of FBG and temperature in this paper, and the simulation results illustrate effectiveness of the presented method compared with least square method.
Keywords :
Bragg gratings; fibre optic sensors; least squares approximations; temperature sensors; FBG sensor; damage loss; fiber Bragg grating sensors; least square method; mass data; monitoring system; relevance vector machine; structural distortion; structure health condition; temperature prediction; Fiber gratings; Kernel; Monitoring; Support vector machines; Temperature distribution; Temperature sensors; FBG sensor; relevance vector machine; temperature prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Management, Innovation Management and Industrial Engineering (ICIII), 2012 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4673-1932-4
Type :
conf
DOI :
10.1109/ICIII.2012.6339689
Filename :
6339689
Link To Document :
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