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Distributed Fibre Optic Sensing Technologies and Applications

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

Deadline for manuscript submissions: 25 March 2025 | Viewed by 19453

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Special Issue Editors

Dr. Martin Litzenberger

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Guest Editor

AIT Austrian Institute of Technology GmbH, Giefinggasse 4, Vienna, Austria
Interests: distributed acoustic sensing; acoustic signal detection and classification; intelligent transportation systems; fibre optic sensors; object detection and tracking

Dr. Gaetan Calbris

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Guest Editor

FEBUS Optics, 2 Avenue du Président Pierre Angot, 64 000 Pau, France
Interests: distributed fibre optics sensing; laser optics

Dr. Bernd Drapp

E-Mail Website
Guest Editor

AP Sensing GmbH, Herrenberger Str. 130, 71034 Böblingen, Germany
Interests: fiber optic sensing applications; interrogator technologies; artificial intelligence (meta learner; zero shot learner)

Special Issue Information

Dear Colleagues,

Originating from the oil and gas industry, all variations of distributed fibre optic sensing, including acoustic sensing (FOAS), temperature sensing (DTS) and strain sensing (DSS), have made steady progress into new domains of long-range sensing applications. Optical interrogator technology, the basis for the distributed fibre optic sensing technologies, has advanced tremendously in recent years. Machine learning is widely considered a gamechanger for the detection and classification of events of interest in the complex FOAS signal. Implementation of real time processing and raw data storage is still challenging, as it must cope with the extremely high amounts of data produced by fibre optic sensing systems.

This Special Issue therefore aims to collect original research and review articles on recent advances, technologies, solutions, applications, and new challenges in the field of distributed fibre optic sensing.

Dr. Martin Litzenberger
Dr. Gaetan Calbris
Dr. Bernd Drapp
Guest Editors

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Keywords

specialised fibre optic cables, sensing fibres
interrogator instrumentation design
amplification and range extension techniques for interrogator systems
raw optical signal processing
object and event detection and classification in FOS signals, including, but not limited to, machine learning techniques
real time parallel processing and signal compression techniques for FOS
railway applications
road traffic monitoring applications
oil and gas applications, including pipeline monitoring
geology applications
border and perimeter surveillance
cable monitoring, including monitoring of power line interconnections
structural health monitoring
long terminal monitoring
power cable or bus duct temperature monitoring
monitoring of offshore windfarms and connections
long term experience or new applications using FOS-based fire detection solutions (e.g., metro tunnels, traffic tunnels, vessels, etc.)
bridge monitoring and condition-based maintenance
monitoring of landslides
dike and dam monitoring

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Published Papers (10 papers)

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10 pages, 2304 KiB

Open AccessCommunication

Few-Shot Classification with Meta-Learning for Urban Infrastructure Monitoring Using Distributed Acoustic Sensing

by Huynh Van Luong, Nikos Deligiannis, Roman Wilhelm and Bernd Drapp

Sensors 2024, 24(1), 49; https://doi.org/10.3390/s24010049 - 21 Dec 2023

Cited by 1 | Viewed by 1591

Abstract

This paper studies an advanced machine learning method, specifically few-shot classification with meta-learning, applied to distributed acoustic sensing (DAS) data. The study contributes two key aspects: (i) an investigation of different pre-processing methods for DAS data and (ii) the implementation of a neural network model based on meta-learning to learn a representation of the processed data. In the context of urban infrastructure monitoring, we develop a few-shot classification framework that classifies query samples with only a limited number of support samples. The model consists of an embedding network trained on a meta dataset for feature extraction and is followed by a classifier for performing few-shot classification. This research thoroughly explores three types of data pre-processing, that is, decomposed phase, power spectral density, and frequency energy band, as inputs to the neural network. Experimental results show the efficient learning capabilities of the embedding model when working with various pre-processed data, offering a range of pre-processing options. Furthermore, the results demonstrate outstanding few-shot classification performance across a large number of event classes, highlighting the framework’s potential for urban infrastructure monitoring applications. Full article

(This article belongs to the Special Issue Distributed Fibre Optic Sensing Technologies and Applications)

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22 pages, 13008 KiB

Open AccessArticle

Characterization of Shallow Ground in Railway Embankments Using Surface Waves Measured by Dark Fiber Optics Sensors: A Case Study

by Edwin Obando Hernandez, Paul Hölscher, Pieter Doornenbal, Cees-jan Mas, Joost van ‘t Schip and Agnes van Uitert

Sensors 2023, 23(23), 9397; https://doi.org/10.3390/s23239397 - 25 Nov 2023

Cited by 1 | Viewed by 1595

Abstract

For the maintenance of railways on soft soils, accurate knowledge of the subsoil conditions is essential. Soft soils at shallow depths have high variability; thus, high spatial resolution is required. Spare telecommunication fiber-optic cables, known as dark fiber, can be used as an array of sensors to measure waves generated by running trains, which offers a unique opportunity to characterize shallow soils at high spatial resolution. We used dark fiber to measure seismic waves generated by running trains and implemented a seismic interferometry technique to retrieve surface waves. We evaluated the reliability of selected parts of the recorded signals split as bow waves (the train approaching the fiber), train waves (the train passing alongside the fiber), and tail waves (the train leaving the fiber) to retrieve broad-band surface waves. The analysis was performed in two distinctive zones. Zone I consists of a thick–soft (2.0–6.0 m thickness) layer, and Zone II consists of a thin–soft (less than 2.0 m thickness) layer, both overlaying a “stiffer” sand layer. At Zone I, train waves yielded the best results in revealing the thick–soft layer. At Zone II, the bow waves yielded clear high-frequency energy, revealing the overall soil structure but without identifying the shallow thin–soft layer. Full article

(This article belongs to the Special Issue Distributed Fibre Optic Sensing Technologies and Applications)

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17 pages, 1989 KiB

Open AccessArticle

A Comprehensive Study on Measurement Accuracy of Distributed Fiber Optic Sensors Embedded within Capillaries of Solid Structures

by Yuzhe Xiao, Calvin Rans, Dimitrios Zarouchas and Rinze Benedictus

Sensors 2023, 23(19), 8083; https://doi.org/10.3390/s23198083 - 26 Sep 2023

Viewed by 1069

Abstract

Embedding fiber optic sensors (FOSs) within parts for strain measurement is attracting widespread interest due to its great potential in the field of structural health monitoring (SHM). This work proposes a novel method of embedding FOSs using capillaries within solid structures and investigates fiber positions and orientation uncertainties within capillaries of different sizes and their influences on strain measurement accuracies. To investigate how the fiber positions and orientation variations influence strain measurement accuracy, both analytical and numerical models are utilized to predict strain distributions along embedded fibers at different positions and with different orientations within the specimen. To verify the predictions, a group of specimens made of Aluminum 6082 was prepared, and the specimens in each group had capillaries of 2 mm, 4 mm, and 6 mm diameters, respectively. Fibers were embedded within each specimen using the capillaries. Four-point bending static tests were conducted for each specimen with embedded FOSs, performing in situ strain measurement. Subsequently, the specimens were partitioned into several pieces, and the cross sections were observed to know the real positions of the embedded fiber. Finally, the strain predictions at the real locations of the fiber were compared with the measured strain from the embedded FOSs. The predicted strain distributions as a function of the fiber positions alone and as a function of both the fiber positions and orientations were compared to assess the influence of fiber orientation change. The results from a combination of analytical, numerical, and experimental techniques suggest that the fiber position from the capillary center is the main factor that can influence strain measurement accuracies of embedded FOSs, and potential fiber misalignments within the capillary had a negligible influence. The fiber position-induced measured error increases from 10.5% to 18.5% as the capillary diameter increases from 2 mm to 6 mm. A 2 mm capillary diameter is able to lead to the lowest measurement error in this study and maintains ease of embedding. In addition, it is found that the measured strain always lies within a strain window defined by the strain distribution along capillary boundaries when there are no cracks. This can be further studied for crack detection. Full article

(This article belongs to the Special Issue Distributed Fibre Optic Sensing Technologies and Applications)

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14 pages, 4362 KiB

Open AccessArticle

How the Material Characteristics of Optical Fibers and Soil Influence the Measurement Results of Distributed Acoustic Sensing

by Ke Jiang, Lei Liang, Xiaoling Tong, Feiyu Zeng and Xiaolong Hu

Sensors 2023, 23(17), 7340; https://doi.org/10.3390/s23177340 - 23 Aug 2023

Cited by 1 | Viewed by 1404

Abstract

Fiber optic distributed acoustic sensing (DAS) technology is widely used in security surveillance and geophysical survey applications. The response of the DAS system to external vibrations varies with different types of fiber optic cable connections. The mechanism of mutual influence between the cable’s characteristics and DAS measurement results remains unclear. This study proposed a dynamic model of the interaction between the optical cable and the soil, analyzed the impact of the dynamic parameters of the optical cable and soil on the sensitivity of the DAS system, and validated the theoretical analysis through experiments. The findings suggest that augmenting the cable’s bending stiffness 5.5-fold and increasing its unit mass 4.2-fold result in a discernible reduction of the system’s response to roughly 0.15 times of its initial magnitude. Cables with lower unit mass and bending stiffness are more sensitive to vibration signals. This research provides a foundation for optimizing vibration-enhanced fiber optic cables and broadening the potential usage scenarios for DAS systems. Full article

(This article belongs to the Special Issue Distributed Fibre Optic Sensing Technologies and Applications)

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15 pages, 1099 KiB

Open AccessArticle

Distributed Poloidal Magnetic Field Measurement in Tokamaks Using Polarization-Sensitive Reflectometric Fiber Optic Sensor

by Prasad Dandu, Andrei Gusarov, Willem Leysen, Perry Beaumont, Marc Wuilpart and JET Contributors

Sensors 2023, 23(13), 5923; https://doi.org/10.3390/s23135923 - 26 Jun 2023

Viewed by 1433

Abstract

Determination of the poloidal magnetic field distribution in tokamaks is of prime importance for the successful operation of tokamaks. In this paper, we propose a polarization-sensitive reflectometry-based optical fiber sensor for measuring the spatial distribution of the poloidal magnetic field in tokamaks. The measurement method exploits the Rayleigh backscattering and Faraday magneto-optic effect in optical fibers. The former is an intrinsic property of optical fibers and enables distributed polarization measurements, while the latter arises in the presence of a magnetic field parallel to the optical fiber axis and rotates the polarization state of the light. When an optical fiber is looped around a toroidal section of the vacuum vessel, the local polarization rotation of the light is proportional to the local poloidal magnetic field in the tokamak. The proposed method is discussed theoretically and experimentally using the results from JET. The obtained magnetic field measurement shows a good agreement with that of the internal discrete coils. A potential solution to recover the magnetic field data from the noise-affected region of the optical measurement is proposed and is demonstrated through simulations using the JET magnetic field configuration. Full article

(This article belongs to the Special Issue Distributed Fibre Optic Sensing Technologies and Applications)

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15 pages, 5790 KiB

Open AccessArticle

Understanding Seepage in Levees and Exploring the Applicability of Using an Optical-Fiber Distributed Temperature System and Smoothing Technique as a Monitoring Method

by Woochul Kang

Sensors 2023, 23(10), 4780; https://doi.org/10.3390/s23104780 - 16 May 2023

Cited by 1 | Viewed by 1154

Abstract

This study aimed to experimentally understand the seepage mechanism in levees and evaluate the applicability of an optical-fiber distributed temperature system based on Raman-scattered light as a levee stability monitoring method. To this end, a concrete box capable of accommodating two levees was built, and experiments were conducted by supplying water evenly to both levees through a system equipped with a butterfly valve. Water-level and water-pressure changes were monitored every minute using 14 pressure sensors, while temperature changes were monitored using distributed optical-fiber cables. Levee 1, composed of thicker particles, experienced a faster water pressure change, and a corresponding temperature change was observed due to seepage. While the temperature change inside the levees was relatively smaller than external temperature changes, measurement fluctuations were significant. Additionally, the influence of external temperature and the dependence of temperature measurements on the levee position made intuitive interpretation challenging. Therefore, five smoothing techniques with different time intervals were examined and compared to determine their effectiveness in reducing outliers, elucidating temperature change trends and enabling the comparison of temperature changes at different positions. Overall, this study confirmed that the optical-fiber distributed temperature system combined with appropriate data-processing techniques can be more efficient than existing methods for understanding and monitoring levee seepage. Full article

(This article belongs to the Special Issue Distributed Fibre Optic Sensing Technologies and Applications)

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18 pages, 16545 KiB

Open AccessArticle

On the Comparison of Records from Standard and Engineered Fiber Optic Cables at Etna Volcano (Italy)

by Sergio Diaz-Meza, Philippe Jousset, Gilda Currenti, Christopher Wollin, Charlotte Krawczyk, Andy Clarke and Athena Chalari

Sensors 2023, 23(7), 3735; https://doi.org/10.3390/s23073735 - 4 Apr 2023

Cited by 2 | Viewed by 2178

Abstract

Distributed Dynamic Strain Sensing (DDSS), also known as Distributed Acoustic Sensing (DAS), is becoming a popular tool in array seismology. A new generation of engineered fibers is being developed to improve sensitivity and reduce the noise floor in comparison to standard fibers, which are conventionally used in telecommunication networks. Nevertheless, standard fibers already have extensive coverage around the Earth’s surface, so it motivates the use of the existing infrastructure in DDSS surveys to avoid costs and logistics. In this study, we compare DDSS data from stack instances of standard multi-fiber cable with DDSS data from a co-located single-fiber engineered cable. Both cables were buried in an area located 2.5 km NE from the craters of Mt. Etna. We analyze how stacking can improve signal quality. Our findings indicate that the stack of DDSS records from five standard fiber instances, each 1.5 km long, can reduce optical noise of up to 20%. We also present an algorithm to correct artifacts in the time series that stem from dynamic range saturation. Although stacking is able to reduce optical noise, it is not sufficient for restoring the strain-rate amplitude from saturated signals in standard fiber DDSS. Nevertheless, the algorithm can restore the strain-rate amplitude from saturated DDSS signals of the engineered fiber, allowing us to exceed the dynamic range of the record. We present measurement strategies to increase the dynamic range and avoid saturation. Full article

(This article belongs to the Special Issue Distributed Fibre Optic Sensing Technologies and Applications)

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29 pages, 7174 KiB

Open AccessArticle

Core versus Surface Sensors for Reinforced Concrete Structures: A Comparison of Fiber-Optic Strain Sensing to Conventional Instrumentation

by Ryan Hoult, Alex Bertholet and João Pacheco de Almeida

Sensors 2023, 23(3), 1745; https://doi.org/10.3390/s23031745 - 3 Feb 2023

Cited by 9 | Viewed by 2694

Abstract

High-resolution distributed reinforcement strain measurements can provide invaluable information for developing and evaluating numerical and analytical models of reinforced concrete structures. A recent testing campaign conducted at UCLouvain in Belgium used fiber-optic sensors embedded along several longitudinal steel rebars of three reinforced concrete U-shaped walls. The resulting experimental dataset provides an opportunity to evaluate and compare, for different types of loading, the strain measurements obtained with the fiber-optic sensors in the confined core of the structural member against more conventional and state-of-the-practice sensors that monitor surface displacements and deformations. This work highlights the need to average strain measurements from digital image correlation techniques in order to obtain coherent results with the strains measured from fiber optics, and investigates proposals to achieve this relevant goal for research and engineering practices. The longitudinal strains measured by the fiber optics also provide additional detailed information on the behavior of these wall units compared to the more conventional instrumentation, such as strain penetration into the foundation and head of the wall units, which are studied in detail. Full article

(This article belongs to the Special Issue Distributed Fibre Optic Sensing Technologies and Applications)

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12 pages, 1129 KiB

Open AccessArticle

Fiber Optic Sensing Textile for Strain Monitoring in Composite Substrates

by Andres Biondi, Rui Wu, Lidan Cao, Balaji Gopalan, Jackson Ivey, Camila Garces, Michael Mitchell, John D. Williams and Xingwei Wang

Sensors 2022, 22(23), 9262; https://doi.org/10.3390/s22239262 - 28 Nov 2022

Cited by 10 | Viewed by 2321

Abstract

Composite polymers have become widely used in industries such as the aerospace, automobile, and civil construction industries. Continuous monitoring is essential to optimize the composite components’ performance and durability. This paper describes the concept of a distributed fiber optic smart textile (DFOST) embedded into a composite panel that can be implemented during the fabrication process of bridges, planes, or vehicles without damaging the integrity of the composite. The smart textile used an embroidery method to create DFOST for easy installation between composite laminates. It also allows different layout patterns to provide two- or three-dimensional measurements. The DFOST system can then measure strain, temperature, and displacement changes, providing critical information for structural assessment. The DFOST was interrogated by using an optical frequency domain reflectometry (OFDR). It could measure strain variation during the dynamic and static test with a spatial resolution of 2 mm and a minimum strain resolution of 10

μ ϵ

. This paper focuses on the study of strain measurement. Full article

(This article belongs to the Special Issue Distributed Fibre Optic Sensing Technologies and Applications)

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16 pages, 4922 KiB

Open AccessArticle

Investigation of High-Resolution Distributed Fiber Sensing System Embedded in Flexible Silicone Carpet for 2D Pressure Mapping

by Zhanerke Katrenova, Shakhrizat Alisherov, Turar Abdol, Madina Yergibay, Zhanat Kappassov, Daniele Tosi and Carlo Molardi

Sensors 2022, 22(22), 8800; https://doi.org/10.3390/s22228800 - 14 Nov 2022

Cited by 9 | Viewed by 2086

Abstract

Fiber-optic sensors are a powerful tool to investigate physical properties like temperature, strain, and pressure. Such properties make these sensors interesting for many applications including biomedical applications. Fiber sensors are also a great platform for distributed sensing by using the principles of optical frequency domain reflectometry. Distributed sensing is becoming more and more used to achieve high-resolution measurements and to map physical properties of biomaterials at small scale, thus obtaining 2D and 3D mapping of a particular area of interest. This work aims at building and investigating a 2D sensing carpet based on a distributed fiber sensing technique, to map local pressure applied to the carpet. The two-dimensional mapping is obtained by embedding a single-mode optical fiber inside a soft silicone carpet. The fiber has been bent and arranged in a specific configuration characterized by several parallel lines. Different fiber fixation methods have been investigated by means of a comparative analysis to perform better characterization and to achieve a more precise response of the carpet. The best pressure sensitivity coefficient (0.373 pm/kPa or considering our setup 1.165 nm/kg) was detected when the fiber was fully embedded inside the silicone carpet. This paper demonstrates the possibility of mapping a 2D distributed pressure over a surface with a resolution of 2 mm by 2 mm. The surface of investigation is 2 cm by 6 cm, containing 310 sensing points. The sensing carpet has been validated selecting several preferential positions, by testing the consistency of the results over different portions of the carpet. Full article

(This article belongs to the Special Issue Distributed Fibre Optic Sensing Technologies and Applications)

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