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Intelligent Distributed Optical Fiber Sensing in Transportation Infrastructures: Research Progress, Applications, and Challenges

Xin Gui, Fanhao Zeng, Yunchuan Zhang, Yiming Wang, Jiaqi Wang, Changjia Wang, Xuelei Fu, Sheng Li, Fang Liu, Lina Yue, Jinpeng Jiang, Zhengying Li

TL;DR

Transportation infrastructures require continuous, long-distance SHM with multi-parameter sensing and EMI immunity. This paper surveys DOFS solutions, including fiber designs (FBG arrays, scattering-enhanced fibers, and laser-modified fibers), cabling packaging, sensing principles (Rayleigh, Brillouin, Raman) and signal processing, and anomaly detection infers. It highlights physics-informed DOFS deployments on railways, expressways, and bridges, and ML-enabled pipelines that convert DOFS data into actionable perception tasks with high accuracy. The review consolidates case studies for train traffic, track, pavement, and bridge monitoring, and outlines roadmaps for reliability, hardware integration, and standardization of OFS technologies. Collectively, the work advances understanding of how DOFS can enable scalable, autonomous intelligent transportation monitoring.

Abstract

Distributed optical fiber sensing (DOFS), along with its capabilities of long-range coverage, multi-parameter monitoring, and completely passive detection, emerges as one of the most promising non-destructive detection techniques for structural health monitoring (SHM) and operational assessment of linear transportation infrastructures. In this paper, we provide a state-of-the-art review on DOFS applications across typical linear infrastructure systems, encompassing highways, long-span bridges, rail transit networks, airport runways, and analogous linear structures. The comprehensive discussion consists of four critical research dimensions: 1) optical fiber selection for multi-parameter sensing and robust cable packaging techniques, 2) distributed sensing principles and signal processing algorithms, 3) diverse application scenarios in SHM and related fields, and 4) anomaly detection and event classification methodologies. Building upon the foundational introduction of DOFS technical principles and monitoring solutions for intelligent transportation infrastructure, this paper elaborates on system design approaches, sensing data analytics algorithms, and future research directions.

Intelligent Distributed Optical Fiber Sensing in Transportation Infrastructures: Research Progress, Applications, and Challenges

TL;DR

Transportation infrastructures require continuous, long-distance SHM with multi-parameter sensing and EMI immunity. This paper surveys DOFS solutions, including fiber designs (FBG arrays, scattering-enhanced fibers, and laser-modified fibers), cabling packaging, sensing principles (Rayleigh, Brillouin, Raman) and signal processing, and anomaly detection infers. It highlights physics-informed DOFS deployments on railways, expressways, and bridges, and ML-enabled pipelines that convert DOFS data into actionable perception tasks with high accuracy. The review consolidates case studies for train traffic, track, pavement, and bridge monitoring, and outlines roadmaps for reliability, hardware integration, and standardization of OFS technologies. Collectively, the work advances understanding of how DOFS can enable scalable, autonomous intelligent transportation monitoring.

Abstract

Distributed optical fiber sensing (DOFS), along with its capabilities of long-range coverage, multi-parameter monitoring, and completely passive detection, emerges as one of the most promising non-destructive detection techniques for structural health monitoring (SHM) and operational assessment of linear transportation infrastructures. In this paper, we provide a state-of-the-art review on DOFS applications across typical linear infrastructure systems, encompassing highways, long-span bridges, rail transit networks, airport runways, and analogous linear structures. The comprehensive discussion consists of four critical research dimensions: 1) optical fiber selection for multi-parameter sensing and robust cable packaging techniques, 2) distributed sensing principles and signal processing algorithms, 3) diverse application scenarios in SHM and related fields, and 4) anomaly detection and event classification methodologies. Building upon the foundational introduction of DOFS technical principles and monitoring solutions for intelligent transportation infrastructure, this paper elaborates on system design approaches, sensing data analytics algorithms, and future research directions.
Paper Structure (15 sections, 2 figures, 6 tables)

This paper contains 15 sections, 2 figures, 6 tables.

Table of Contents

  1. Introduction
  2. Sensing Optical Fiber Preparation and Sensing Optical Cable Packaging Methods
  3. DOFS Based on Fiber Bragg Grating Array
  4. Scattering-Enhanced Sensing Fibers for Increasing the Scattering Coefficient
  5. Sensing Fibers Based on Laser Modification Technology
  6. Distributed Sensing Optical Cables
  7. Distributed Temperature Sensing Optical Cables
  8. Distributed Strain Sensing Optical Cables
  9. Vibration/Acoustic Sensing Optical Cables
  10. Recent Advances in OFS for Intelligent Transportation Infrastructures
  11. Physics-Informed OFS for Transportation Infrastructures
  12. Train traffic and operation monitoring
  13. Track Substructure Condition Measurements and Intrusion Detection
  14. Machine Learning-Enabled OFS for Intelligent Transportation Infrastructures
  15. Conclusion

Figures (2)

  • Figure 1: Spectra of various types of UWFBG array fabricated via the drawing tower process. (a) Apodized FBGs array, (b) chirped FBGs array, (c) ultra-short FBGs array, (d) multi-wavelength FBGs array.
  • Figure 2: Strain transfer mechanism in a surface-bonded multi-layered distributed FO sensor. (a) Cross section. (b) Stress state of a cable element3205zheng2021strain.