Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 39,
  • Issue 18,
  • pp. 5988-5994
  • (2021)

Sensitivity Enhancement of Fiber-Optic Accelerometers Using Thin-Cladding Fiber Bragg Gratings

Not Accessible

Your library or personal account may give you access

Abstract

We propose and demonstrate a method for improving the sensitivity of fiber Bragg grating (FBG) based accelerometers. The method employs a short FBG inscribed in single mode fiber (SMF) with cladding substantially thinner than 125 μm. The resultant stress concentration at the FBG significantly improved the axial strain response compared with 125-μm-diameter fiber. A 50-μm-diameter FBG fixed on a cantilever beam was used to experimentally demonstrate this sensitivity enhancement. The accelerometer has a working frequency bandwidth from 0.5 Hz to 30 Hz with a sensitivity of 2150±30 pm/g, amounting to 5-fold sensitivity enhancement compared to 125-μm-diameter fiber.

PDF Article
More Like This
Very sensitive fiber Bragg grating accelerometer using transverse forces with an easy over-range protection and low cross axial sensitivity

Kuo Li, Tommy H. T. Chan, Man Hong Yau, Theanh Nguyen, David P. Thambiratnam, and Hwa Yaw Tam
Appl. Opt. 52(25) 6401-6410 (2013)

Orientation-dependent fiber-optic accelerometer based on eccentric fiber Bragg grating

Fengyi Chen, Ruohui Wang, Xingyong Li, and Xueguang Qiao
Opt. Express 29(18) 28574-28581 (2021)

Sensitivity enhanced vector accelerometer based on FBG-FP inscribed on multicore fiber

Jiaojiao Wang, Fengyi Chen, Rui Zhou, Ruohui Wang, and Xueguang Qiao
Appl. Opt. 62(6) 1592-1597 (2023)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.