Radiation enhanced sensitivity of temperature and curvature sensor based on Bi/Er Co-doped fibre with ultra-broadband emission
Date
2025
Authors
Huang, Z.
Luo, Y.
Wen, J.
Wang, T.
Mou, C.
Chen, W.
Wei, S.
Zou, W.
Sun, X.
Azmi, A.I.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
Measurement: Journal of the International Measurement Confederation, 2025; 254:117936-1-117936-15
Statement of Responsibility
Zhexu Huang, Yanhua Luo, Jianxiang Wen, Tingyun Wang, Chengbo Mou, Wei Chen, Shuen Wei, Weiwen Zou, Xiaohong Sun, Asrul Izam Azmi, Gang-Ding Peng
Conference Name
Abstract
To accommodate the growing scale and diverse applications of fibre optic sensing networks, a temperature and curvature sensing system suitable for radiation environment is proposed based on Bi/Er co-doped fibre (BEDF) with offset-core and ultra-broadband emission. First, two sections of BEDFs were employed to construct an ultra-broadband light source and a Mach-Zehnder Interferometer (MZI) for the sensing system, respectively. Then, the sensing performance of the MZI was evaluated through simulations and experiment. Especially, the impact of gamma radiation on sensing characteristics was evaluated by comparing MZI sensors based on irradiated and non-irradiated BEDFs. Both simulations and experiment results confirmed that the sensitivity improved due to an increase of the refractive index for the fibre core of BEDF, attributed to radiation-induced refractive index change. The sensing results indicate that for the irradiated BEDF based sensor, the maximum temperature sensitivity at 1592 nm was up to 90 pm/℃ with an increase of 50 %, while the maximum curvature sensitivity at 1550 nm was 5.66 nm/m¯¹ with an increase of 226 %, respectively. Such sensitivity enhancement further demonstrates that 50 kGy gamma ray irradiated BEDF had an increase of effective refractive index of 10¯³ order. Moreover, the proposed MZI sensing system, featuring a broadband near-infrared emission exceeding 500 nm, exhibits great potential for temperature and curvature detection in the Internet of Things (IoT) and ultra-large-scale sensor networks.
School/Discipline
Dissertation Note
Provenance
Description
Access Status
Rights
© 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.