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Applied Sciences
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Advanced Optical Fiber Sensors: Applications and Technology
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Advanced Optical Fiber Sensors: Applications and Technology

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 928

Special Issue Editors

Dr. Xiangge He

E-Mail Website
Guest 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 Issues, Collections and Topics in MDPI journals
Dr. Kunpeng Zhang

E-Mail Website
Guest Editor
Beijing International Center for Gas Hydrate, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Interests: fiber optic sensing; hydraulic fracturing; flow rate measuring; wellbore stability; rock mechanics; porous seepage
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Optical fiber sensing has made remarkable progress in recent years and holds great promise for the future. Its ability to detect changes in temperature, strain, pressure, and various physical and chemical parameters has established optical fiber sensing as a vital technology across multiple fields, including structural health monitoring, industrial process control, and environmental sensing. Recent advancements in fiber optic technology, signal processing, and sensing algorithms have significantly enhanced the sensitivity, accuracy, and reliability of optical fiber sensors. Additionally, the development of innovative materials, such as fiber Bragg gratings and photonic crystal fibers, has broadened the range of applications for optical fiber sensing.

As research in this field progresses, optical fiber sensing is expected to play an increasingly pivotal role in tackling various societal challenges, including infrastructure monitoring, energy efficiency, and healthcare.

This Special Issue aims to compile original research and review articles on recent advances, technologies, solutions, applications, and emerging challenges in the field of optical fiber sensing. Topics will include, but are not limited to, the following:

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

Dr. Xiangge He
Dr. Kunpeng Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

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

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Published Papers (2 papers)

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Research

12 pages, 4468 KB  
Article
Binary-Tree Structure for Extended Range-Distributed Acoustic Sensing
by Xiangge He, Zhi Cao, Min Zhang and Hailong Lu
Appl. Sci. 2025, 15(21), 11748; https://doi.org/10.3390/app152111748 - 4 Nov 2025
Viewed by 323
Abstract
The dual-pulse heterodyne demodulation distributed acoustic sensing (HD-DAS) system has superior performance but is fundamentally limited by the short sensing range, which poses a significant obstacle to its application in long-distance monitoring. This paper proposes and experimentally demonstrates a novel binary-tree structure DAS [...] Read more.
The dual-pulse heterodyne demodulation distributed acoustic sensing (HD-DAS) system has superior performance but is fundamentally limited by the short sensing range, which poses a significant obstacle to its application in long-distance monitoring. This paper proposes and experimentally demonstrates a novel binary-tree structure DAS (BTS-DAS) aimed at overcoming this critical limitation. By physically decoupling the long-distance transmission fiber from the final sensing part, this structure effectively expands the system’s remote sensing capability without compromising the high pulse repetition rate for high-performance measurement. We identified modulation instability (MI), rather than stimulated Brillouin scattering (SBS), as the dominant nonlinear noise source in the extended fiber chain. Through careful power management, we established an optimal launch power window. The practical feasibility of the system was verified during on-site testing, where vibrations were successfully detected over a 10 km transmission link with sensing occurring in the 250 m sensing fiber segment, achieving a low background noise of −59.79 dB ref rad/Hz. This work presents a robust and scalable solution for long-range, high-performance acoustic sensing. Full article
(This article belongs to the Special Issue Advanced Optical Fiber Sensors: Applications and Technology)
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17 pages, 2923 KB  
Article
TY-SpectralNet: An Interpretable Adaptive Network for the Pattern of Multimode Fiber Spectral Analysis
by Yuzhe Wang, Songlu Lin, Fudong Zhang and Zhihong Wang
Appl. Sci. 2025, 15(19), 10606; https://doi.org/10.3390/app151910606 - 30 Sep 2025
Viewed by 380
Abstract
Background: The high-precision analysis of multimode fibers (MMFs) is a critical task in numerous applications, including remote sensing, medical imaging, and environmental monitoring. In this study, we propose a novel deep interpretable network approach to reconstruct spectral images captured using CCD sensors. [...] Read more.
Background: The high-precision analysis of multimode fibers (MMFs) is a critical task in numerous applications, including remote sensing, medical imaging, and environmental monitoring. In this study, we propose a novel deep interpretable network approach to reconstruct spectral images captured using CCD sensors. Methods: Our model leverages a Tiny-YOLO-inspired convolutional neural network architecture, specifically designed for spectral wavelength prediction tasks. A total of 1880 CCD interference images were acquired across a broad near-infrared range from 1527.7 to 1565.3 nm. To ensure precise predictions, we introduce a dynamic factor α and design a dynamic adaptive loss function based on Huber loss and Log-Cosh loss. Results: Experimental evaluation with five-fold cross-validation demonstrates the robustness of the proposed method, achieving an average validation MSE of 0.0149, an R2 score of 0.9994, and a normalized error (μ) of 0.0005 in single MMF wavelength prediction, confirming its strong generalization capability across unseen data. The reconstructed outputs are further visualized as smooth spectral curves, providing interpretable insights into the model’s decision-making process. Conclusions: This study highlights the potential of deep learning-based interpretable networks in reconstructing high-fidelity spectral images from CCD sensors, paving the way for advancements in spectral imaging technology. Full article
(This article belongs to the Special Issue Advanced Optical Fiber Sensors: Applications and Technology)
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