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Chin. Opt. Lett.
 Home  List of Issues    Issue 07 , Vol. 16 , 2018    10.3788/COL201816.070604


Hybrid fiber Bragg grating sensor for vibration and temperature monitoring of a train bearing
Xiaofeng Wang1;2, Yongxing Guo3, and Li Xiong4
1 School of Communication, [Shenzhen University], Shenzhen 51 8060, China
2 School of Political Science and Public Management, [Wuhan University], Wuhan 430072 , China
3 Key Laboratory of Metallurgical Equipment and Control Technology, [Ministry of Education, Wuhan University of Science and Technology], Wuhan 43 0081, China
4 Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, [Wuhan University of Science and Technology], Wuhan 4 30081, China

Chin. Opt. Lett., 2018, 16(07): pp.070604

DOI:10.3788/COL201816.070604
Topic:Fiber optics and optical communication
Keywords(OCIS Code): 060.3735  060.2370  280.4788  

Abstract
We report a fiber Bragg grating (FBG)-based sensor for the simultaneous measurement of a train bearing’s vibration and temperature. A pre-stretched optical fiber with an FBG and a mass is designed for axial vibration sensing. Another multiplexed FBG is embedded in a selected copper-based alloy with a high thermal expansion to detect temperature. Experiments show that the sensor possesses a high resonant frequency of 970 Hz, an acceleration sensitivity of 27.28 pm/g, and a high temperature sensitivity of 35.165 pm/°C. A resonant excitation test is also carried out that demonstrates the robustness and reliability of the sensor.

Copyright: © 2003-2012 . This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Received:2018/4/3
Accepted:2018/5/14
Posted online:2018/6/29

Get Citation: Xiaofeng Wang, Yongxing Guo, and Li Xiong, "Hybrid fiber Bragg grating sensor for vibration and temperature monitoring of a train bearing," Chin. Opt. Lett. 16(07), 070604(2018)

Note: This work was supported in part by the National Natural Science Foundation of China (Nos. 51605348 and 51605344), in part by the Natural Science Foundation of the Hubei Province (No. 2016CFB116), and in part by the Open Research Fund of the Hubei Digital Manufacturing Key Laboratory (No. SZ1801).



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