Progress and Prospects in Optical Fiber Sensing

A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "Lasers, Light Sources and Sensors".

Deadline for manuscript submissions: 20 September 2024 | Viewed by 2034

Special Issue Editor

School of Earth and Space Sciences, Peking University, Beijing 100871, China
Interests: optical fiber sensing; distributed acoustic sensor; optical fiber temperature and pressure sensing; sensing applications

Special Issue Information

Dear Colleagues,

Optical fiber sensing has made significant progress in recent years and holds great prospects for the future. With its ability to detect changes in temperature, strain, pressure, and other physical and chemical parameters, this technology has become critical in various fields, including structural health monitoring, industrial process control, and environmental sensing. Advances in fiber optic technology, signal processing, and sensing algorithms have led to improvements in the sensitivity, accuracy, and reliability of optical fiber sensors. Furthermore, the development of new materials, such as fiber Bragg gratings and photonic crystal fibers, has expanded the range of applications. As research in this field continues, it is expected that optical fiber sensing will play an increasingly important role in addressing societal challenges such as infrastructure monitoring, energy efficiency, and healthcare.

This Special Issue aims to bring together original research and review articles on recent advances, technologies, solutions, applications, and new challenges in the field of optical fiber sensing. The topics will include, but are not limited to:

  • Physical, chemical, and biological optical fiber sensors;
  • Interferometric, scattering, and polarimetric optical fiber sensors;
  • Micro- and nanostructured optical fiber sensors;
  • Distributed and multiplexed sensing and sensor networking;
  • Environmental, geophysical, marine, security, defense, and industrial applications.

Dr. Xiangge He
Guest Editor

Manuscript Submission Information

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Keywords

  • optical fiber sensing
  • sensing technology
  • distributed sensing
  • sensor structure
  • applications

Published Papers (2 papers)

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Research

17 pages, 11374 KiB  
Article
A Pattern Recognition Method for Filter Bags in Bag Dust Collectors Based on Φ-Optical Time-Domain Reflectometry
by Xu’an Liu, Yuquan Tang, Zhirong Zhang, Shuang Yang, Zhouchang Hu and Yuan Xu
Photonics 2024, 11(2), 152; https://doi.org/10.3390/photonics11020152 - 05 Feb 2024
Viewed by 697
Abstract
The use of phase-sensitive optical time-domain reflectometry (Φ-OTDR)-distributed fiber vibration sensors to detect and identify damaged bags in bag dust collectors has the potential to overcome the inadequacy of traditional damaged bag detection methods. In our previous study, we verified the feasibility of [...] Read more.
The use of phase-sensitive optical time-domain reflectometry (Φ-OTDR)-distributed fiber vibration sensors to detect and identify damaged bags in bag dust collectors has the potential to overcome the inadequacy of traditional damaged bag detection methods. In our previous study, we verified the feasibility of applying this technique in the field of damaged bag detection in bag filters. However, many problems still occur in engineering applications when using this technology to detect and identify damaged filter bags in pulse-jet dust-cleaning bag dust collectors. Further studies are needed to characterize the fiber vibration signals inside different types of rectangular damaged filter bags. A filter bag damage identification and detection method based on empirical mode decomposition (EMD) and a backpropagation (BP) neural network is proposed. The signal feature differences between intact filter bags and damaged filter bags with different rectangular hole sizes and positions are comparatively analyzed, and optimal feature difference parameters are proposed. Support vector machine (SVM) and a BP neural network are used to recognize different types of filter bag signals, and the comparison results show that the BP neural network algorithm is better at recognizing different types of filter bags, obtaining the highest recognition rate of 97.3%. Full article
(This article belongs to the Special Issue Progress and Prospects in Optical Fiber Sensing)
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13 pages, 5542 KiB  
Article
Fiber Bragg Grating Salinity Sensor Array Based on Fiber Tapering and HF Etching
by Gaochao Li, Yongjie Wang, Mengchao Yan, Tuanwei Xu, Ancun Shi, Yuanhui Liu, Xuechun Li and Fang Li
Photonics 2023, 10(12), 1315; https://doi.org/10.3390/photonics10121315 - 29 Nov 2023
Cited by 2 | Viewed by 926
Abstract
We propose a seawater salinity sensor array based on a micro/nanofiber Bragg grating structures, which allows for the simultaneous measurement of temperature and salinity. The proposed sensing structure is fabricated through a process involving optical fiber tapering, femtosecond laser inscription, and chemical etching. [...] Read more.
We propose a seawater salinity sensor array based on a micro/nanofiber Bragg grating structures, which allows for the simultaneous measurement of temperature and salinity. The proposed sensing structure is fabricated through a process involving optical fiber tapering, femtosecond laser inscription, and chemical etching. The equivalent refractive index (RI) of this sensor structure is influenced by the surrounding RI, resulting in a Bragg characteristic wavelength shift that can be used for salinity sensing. The experimental results show that the salinity sensitivity for two cascaded sensor arrays is 8.39 pm/‰ and 7.71 pm/‰, while the temperature sensitivity is 8.28 pm/°C and 8.03 pm/°C, respectively. This sensor structure is compact, exhibits excellent linearity, and offers good repeatability. It holds great potential for applications in seawater environmental monitoring and quantitative studies of seawater dispersion characteristics. Full article
(This article belongs to the Special Issue Progress and Prospects in Optical Fiber Sensing)
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