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Distributed Optical Fiber Sensing Technology and Applications
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Distributed Optical Fiber Sensing Technology and Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Optical Sensors".

Deadline for manuscript submissions: 15 July 2026 | Viewed by 1067

Special Issue Editors

Prof. Dr. Xuping Zhang

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Guest Editor
1. College of Engineering and Applied Sciences, Nanjing University, Gulou District, Nanjing 210093, China
2. Key Laboratory of Intelligent Optical Sensing and Manipulation, Ministry of Education, Nanjing University, Nanjing 210093, China
Interests: distributed fiber optic sensing principles and technologies; artificial intelligence processing technology for optical sensor signals; distributed hydrophone systems for marine monitoring; applications of fiber optic sensing technology in health monitoring of large-scale engineering infrastructure
Special Issues, Collections and Topics in MDPI journals
Dr. Bo Liu

E-Mail Website
Guest Editor
1. Research Center for Novel Computing Sensing and Intelligent Processing, Zhejiang Lab, Hangzhou 311100, China
2. State Key Laboratory of Extreme Photonics and Instrumentation and College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China
Interests: intelligence of data driven; intelligent sensing; distributed temperature sensing; fiber optics sensing; machine learning in signal processing; single crystal fiber; AI enabled sensing technologies
Special Issues, Collections and Topics in MDPI journals
Dr. Lingmei Ma

E-Mail Website1 Website2
Guest Editor
Westlake Institute for Optoelectronics, Westlake University, Hangzhou 310024, China
Interests: optical fiber sensing
Prof. Dr. Jun He

E-Mail Website
Guest Editor
Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors, Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education/Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
Interests: distributed acoustic sensors; distributed temperature sensors; phase-sensitive optical time-domain reflectometry; Raman-based optical time-domain reflectometry; fiber-optic sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Distributed fiber optic sensing (DOFS) technology transforms standard optical fibers into continuous sensing media, enabling real-time, simultaneous measurement of temperature, strain, vibration, and acoustic signals at any point along tens of kilometers of fiber. As a landmark technology in international competitive strategy, DOFS has emerged as the most ideal non-destructive monitoring solution for large-scale infrastructure across critical sectors, including energy, power, aerospace, communications, transportation, and security. This Special Issue seeks to present cutting-edge research and innovative applications that advance this rapidly evolving field, highlighting its unique advantages for infrastructure health monitoring and environmental sensing. We invite original research and review articles addressing theoretical advances, technological innovations, and practical applications in DOFS：

  1. Distributed Fiber Optic Sensor Devices and Modules;
  2. Distributed Fiber Optic Sensing Principles and Systems;
  3. Applications in Civil Engineering and Transportation;
  4. Applications in the Energy Sector;
  5. Applications in Public Safety and Natural Disaster Management;
  6. Applications in Marine Monitoring;
  7. Applications in Aerospace;
  8. Special Fiber Optic Cables for Distributed Fiber Optic Sensing.

Prof. Dr. Xuping Zhang
Dr. Bo Liu
Dr. Lingmei Ma
Prof. Dr. Jun He 
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. Sensors 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 2600 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

  • fiber optic
  • distributed fiber optic sensing
  • sensing

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Published Papers (1 paper)

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Research

31 pages, 5068 KB  
Article
Experimental Laboratory Study on the Acoustic Response Characteristics of Fluid Flow in Horizontal Wells Based on Distributed Fiber Optic Sensing
by Geyitian Feng, Zhengting Yan, Jixin Li, Yang Ni, Manjiang Li, Zhanzhu Li, Xin Huang, Junchao Li, Qinzhuo Liao and Xu Liu
Sensors 2026, 26(7), 2248; https://doi.org/10.3390/s26072248 - 5 Apr 2026
Viewed by 478
Abstract
Distributed acoustic sensing (DAS) has been widely applied to injection–production profile monitoring in horizontal wells because it provides continuous full-wellbore coverage, real-time acquisition, and straightforward long-term deployment. In practical downhole operations, however, DAS measurements are frequently compromised by optical-signal attenuation, loss of fiber–casing/formation [...] Read more.
Distributed acoustic sensing (DAS) has been widely applied to injection–production profile monitoring in horizontal wells because it provides continuous full-wellbore coverage, real-time acquisition, and straightforward long-term deployment. In practical downhole operations, however, DAS measurements are frequently compromised by optical-signal attenuation, loss of fiber–casing/formation coupling, and environmental noise. Meanwhile, the mechanisms governing flow-induced acoustic responses remain insufficiently understood, which continues to impede quantitative diagnosis and interpretation of injection–production profiles based on DAS data. To address these challenges, this study performed controlled laboratory-scale physical simulation experiments of single-phase flow in a horizontal wellbore, systematically investigating DAS acoustic responses under two wellbore diameters (25 mm and 50 mm) and a range of flow velocities. Power spectral density (PSD) was derived using the fast Fourier transform to identify flow-sensitive characteristic frequency bands, and frequency-band energy (FBE) was further used to establish an optimal quantitative relationship with flow velocity. The results show that: (1) DAS energy is dominated by low-frequency components (<100 Hz), with the total energy increasing nonlinearly as flow velocity rises, accompanied by a progressive broadening of the characteristic bands; (2) the feature bands identified using an adaptive method based on energy difference statistics applied to PSD frequency-domain features exhibit a higher signal-to-noise ratio and greater physical clarity than traditional wide frequency bands; furthermore, by employing a feature band merging strategy, the distribution characteristics of flow energy can be captured more comprehensively; and (3) FBE exhibits a strong nonlinear dependence on flow velocity, with a power-law model delivering the best theoretical fit, whereas a cubic model (FBE ∝ V3) achieves high accuracy and robustness for practical applications. The proposed workflow—“PSD peak identification–characteristic band delineation–FBE regression”—establishes a methodological foundation for quantitative DAS-based monitoring of horizontal-well injection–production profiles in both laboratory and field settings, and it provides a basis for subsequent intelligent monitoring and interpretation under multiphase-flow conditions. Full article
(This article belongs to the Special Issue Distributed Optical Fiber Sensing Technology and Applications)
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