Sensors

Research

13 pages, 1134 KiB

Open AccessArticle

CNN–Aided Optical Fiber Distributed Acoustic Sensing for Early Detection of Red Palm Weevil: A Field Experiment

by Islam Ashry, Biwei Wang, Yuan Mao, Mohammed Sait, Yujian Guo, Yousef Al-Fehaid, Abdulmoneim Al-Shawaf, Tien Khee Ng and Boon S. Ooi

Sensors 2022, 22(17), 6491; https://doi.org/10.3390/s22176491 - 29 Aug 2022

Cited by 9 | Viewed by 2737

Abstract

Red palm weevil (RPW) is a harmful pest that destroys many date, coconut, and oil palm plantations worldwide. It is not difficult to apply curative methods to trees infested with RPW; however, the early detection of RPW remains a major challenge, especially on [...] Read more.

Red palm weevil (RPW) is a harmful pest that destroys many date, coconut, and oil palm plantations worldwide. It is not difficult to apply curative methods to trees infested with RPW; however, the early detection of RPW remains a major challenge, especially on large farms. In a controlled environment and an outdoor farm, we report on the integration of optical fiber distributed acoustic sensing (DAS) and machine learning (ML) for the early detection of true weevil larvae less than three weeks old. Specifically, temporal and spectral data recorded with the DAS system and processed by applying a 100–800 Hz filter are used to train convolutional neural network (CNN) models, which distinguish between “infested” and “healthy” signals with a classification accuracy of ∼97%. In addition, a strict ML-based classification approach is introduced to improve the false alarm performance metric of the system by ∼20%. In a controlled environment experiment, we find that the highest infestation alarm count of infested and healthy trees to be 1131 and 22, respectively, highlighting our system’s ability to distinguish between the infested and healthy trees. On an outdoor farm, in contrast, the acoustic noise produced by wind is a major source of false alarm generation in our system. The best performance of our sensor is obtained when wind speeds are less than 9 mph. In a representative experiment, when wind speeds are less than 9 mph outdoor, the highest infestation alarm count of infested and healthy trees are recorded to be 1622 and 94, respectively. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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13 pages, 2404 KiB

Open AccessArticle

The Characterization of Optical Fibers for Distributed Cryogenic Temperature Monitoring

by Leonardo Marcon, Antonella Chiuchiolo, Bernardo Castaldo, Hugues Bajas, Andrea Galtarossa, Marta Bajko and Luca Palmieri

Sensors 2022, 22(11), 4009; https://doi.org/10.3390/s22114009 - 25 May 2022

Cited by 6 | Viewed by 2474

Abstract

Thanks to their characteristics, optical fiber sensors are an ideal solution for sensing applications at cryogenic temperatures, such as the monitoring of superconducting devices. Their applicability at such temperatures, however, is not immediate as optical fibers exhibit a non-linear thermal response which becomes [...] Read more.

Thanks to their characteristics, optical fiber sensors are an ideal solution for sensing applications at cryogenic temperatures, such as the monitoring of superconducting devices. Their applicability at such temperatures, however, is not immediate as optical fibers exhibit a non-linear thermal response which becomes rapidly negligible below 50 K. A thorough analysis of such a response down to cryogenic temperatures then becomes necessary to correctly translate the optical interrogation readings into the actual fiber temperature. Moreover, to increase the fiber sensitivity down to a few kelvin, special coatings can be used. In this manuscript we described the thermal responses experimental characterization of four commercially available optical fiber samples with different polymeric coatings in the temperature range from 5

K

to 300

K

: two with acrylate coatings of different thickness, one with a polyimide coating and one with a polyether–ether–ketone (PEEK) coating. Multiple thermal cycles were performed consecutively to guarantee the quality of the results and a proper estimate of the sensitivity of the various samples. Finally, we experimentally validated the quality of the measured thermal responses by monitoring the cool down of a dummy superconducting link from room temperature to approximately 50

K

using two fibers coated, respectively, in acrylate and PEEK. The temperatures measured with the fibers agreed and matched those obtained by standard electronic sensors, providing, at the same time, further insight in to the cool-down evolution along the cryostat. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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13 pages, 4055 KiB

Open AccessArticle

A Dynamic Calibration of Optical Fiber DTS Measurements Using PEST and Reference Thermometers

by Yaser Ghafoori, Andrej Vidmar and Andrej Kryžanowski

Sensors 2022, 22(10), 3890; https://doi.org/10.3390/s22103890 - 20 May 2022

Cited by 5 | Viewed by 2471

Abstract

Temperature measurements are widely used in structural health monitoring. Optical fiber distributed temperature sensors (DTS) are developed, based on Raman spectroscopy, to measure temperature with relatively high accuracy and short temporal and spatial resolutions. DTS systems provide an extensive number of temperature measurements [...] Read more.

Temperature measurements are widely used in structural health monitoring. Optical fiber distributed temperature sensors (DTS) are developed, based on Raman spectroscopy, to measure temperature with relatively high accuracy and short temporal and spatial resolutions. DTS systems provide an extensive number of temperature measurements along the entire length of an optical fiber that can be extended to tens of kilometers. The efficiency of the temperature measurement strongly depends on the calibration of the DTS data. Although DTS systems internally calibrate the data, manual calibration techniques were developed to achieve more accurate results. Manual calibration employs reference sections or points with known temperatures and the DTS scattering data to estimate the calibration parameters and calculate temperature along the optical fiber. In some applications, manual calibration is subjected to some shortages, based on the proposed fiber installation configuration and continuity of calibration. In this article, the manual calibration approach was developed using the model-independent Parameters Estimation (PEST), together with the external temperature sensors as references for the DTS system. The proposed method improved manual calibration in terms of installation configuration, continuity of dynamic calibration, and estimation of the calibration parameters. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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10 pages, 4841 KiB

Open AccessArticle

24 km High-Performance Raman Distributed Temperature Sensing Using Low Water Peak Fiber and Optimized Denoising Neural Network

by Hao Wu, Haoze Du, Can Zhao and Ming Tang

Sensors 2022, 22(6), 2139; https://doi.org/10.3390/s22062139 - 10 Mar 2022

Cited by 15 | Viewed by 2441

Abstract

Raman distributed optical fiber temperature sensing (RDTS) has been extensively studied for decades because it enables accurate temperature measurements over long distances. The signal-to-noise ratio (SNR) is the main factor limiting the sensing distance and temperature accuracy of RDTS. We manufacture a low [...] Read more.

Raman distributed optical fiber temperature sensing (RDTS) has been extensively studied for decades because it enables accurate temperature measurements over long distances. The signal-to-noise ratio (SNR) is the main factor limiting the sensing distance and temperature accuracy of RDTS. We manufacture a low water peak optical fiber (LWPF) with low transmission loss to improve the SNR for long-distance application. Additionally, an optimized denoising neural network algorithm is developed to reduce noise and improve temperature accuracy. Finally, a maximum temperature uncertainty of 1.77 °C is achieved over a 24 km LWPF with a 1 m spatial resolution and a 1 s averaging time. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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13 pages, 6302 KiB

Open AccessArticle

High-Accuracy Event Classification of Distributed Optical Fiber Vibration Sensing Based on Time–Space Analysis

by Zhao Ge, Hao Wu, Can Zhao and Ming Tang

Sensors 2022, 22(5), 2053; https://doi.org/10.3390/s22052053 - 7 Mar 2022

Cited by 11 | Viewed by 2566

Abstract

Distributed optical fiber vibration sensing (DVS) can measure vibration information along with an optical fiber. Accurate classification of vibration events is a key issue in practical applications of DVS. In this paper, we propose a convolutional neural network (CNN) to analyze DVS data [...] Read more.

Distributed optical fiber vibration sensing (DVS) can measure vibration information along with an optical fiber. Accurate classification of vibration events is a key issue in practical applications of DVS. In this paper, we propose a convolutional neural network (CNN) to analyze DVS data and achieve high-accuracy event recognition fully. We conducted experiments outdoors and collected more than 10,000 sets of vibration data. Through training, the CNN acquired the features of the raw DVS data and achieved the accurate classification of multiple vibration events. The recognition accuracy reached 99.9% based on the time–space data, a higher than used time-domain, frequency–domain, and time–frequency domain data. Moreover, considering that the performance of the DVS and the testing environment would change over time, we experimented again after one week to verify the method’s generalization performance. The classification accuracy using the previously trained CNN is 99.2%, which is of great value in practical applications. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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13 pages, 4178 KiB

Open AccessArticle

Quantification of DAS VSP Quality: SNR vs. Log-Based Metrics

by Aleksei Titov, Vladimir Kazei, Ali AlDawood, Ezzedeen Alfataierge, Andrey Bakulin and Konstantin Osypov

Sensors 2022, 22(3), 1027; https://doi.org/10.3390/s22031027 - 28 Jan 2022

Cited by 13 | Viewed by 2996

Abstract

The initial quantification of data quality is an important step in seismic data acquisition design, including the choice of sensing strategy. The signal-to-noise ratio (SNR) often drives the choice of distributed acoustic sensing (DAS) parameters in vertical seismic profiling (VSP). We compare this [...] Read more.

The initial quantification of data quality is an important step in seismic data acquisition design, including the choice of sensing strategy. The signal-to-noise ratio (SNR) often drives the choice of distributed acoustic sensing (DAS) parameters in vertical seismic profiling (VSP). We compare this established approach for data quality assessment with metrics comparing DAS data products to available well logs. First, we create kinematic and dynamic data products derived from original seismic data, such as the interval velocity and amplitude of P-wave arrivals. Next, we quantify the quality of derived data products using well log data by calculating various statistical metrics. Using a large dataset of 220 different VSP experiments with a fixed source location and various DAS acquisition parameters, such as gauge length (GL), conveyance type, and lead-in length, we analyzed the statistical distribution of various metrics. The results indicate the decoupling between seismic-based and log-based metrics as well as between the quality of dynamic and kinematic data-products for the same record. Therefore, we propose using fit-for-purpose metrics to optimize the acquisition cost. In particular, for ray-based tomographic processing, it is sufficient to use traveltime-based metrics. On the other hand, for advanced dynamic analysis, amplitude-based metrics define the quality of final processing products. Hence, it is crucial to use fit-for-purpose metrics to optimize DAS VSP acquisition. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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10 pages, 5175 KiB

Open AccessCommunication

Aircraft Detection Using Phase-Sensitive Optical-Fiber OTDR

by Yunpeng Cai, Jihui Ma, Wenfa Yan, Wenyi Zhang and Yuhang An

Sensors 2021, 21(15), 5094; https://doi.org/10.3390/s21155094 - 28 Jul 2021

Cited by 9 | Viewed by 3054

Abstract

Aircraft detection plays a vital role in aviation management and safe operation in the aviation system. Phase-Sensitive Optical Time Domain Reflectometry (Φ-OTDR) technology is a prevailing sensing method in geophysics research, structure inspection, transportation detection, etc. Compared with existing video- or radio-based detection [...] Read more.

Aircraft detection plays a vital role in aviation management and safe operation in the aviation system. Phase-Sensitive Optical Time Domain Reflectometry (Φ-OTDR) technology is a prevailing sensing method in geophysics research, structure inspection, transportation detection, etc. Compared with existing video- or radio-based detection methods, Φ-OTDR is cost-effective, suitable for long-distance detection, and resistant to severe weather conditions. We present a detection system using Φ-OTDR technology and analyze the character of the acoustic signal of aircraft. Instead of runway monitoring in the airport or noise detection in the air, this study focuses on the detection of seismic vibration signal excited by the sound of aircraft. The Chebyshev filter is adopted to eliminate the impact of background noise and random noise from the original vibration signal; the short-time Fourier transform is used for time-frequency analysis. The experimental results showed that the seismic vibration signal excited by the aircraft sound is mainly low-frequency, which is under 5 Hz. Time delay of aircraft vibration signal in different locations of the optic fiber is recorded by the sensing system. The Doppler effect is also revealed by the time-domain analysis: the frequency increases when the aircraft is approaching and decreases when the aircraft moves away. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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12 pages, 10236 KiB

Open AccessCommunication

Ultimate Spatial Resolution Realisation in Optical Frequency Domain Reflectometry with Equal Frequency Resampling

by Zhen Guo, Gaoce Han, Jize Yan, David Greenwood, James Marco and Yifei Yu

Sensors 2021, 21(14), 4632; https://doi.org/10.3390/s21144632 - 6 Jul 2021

Cited by 22 | Viewed by 3563

Abstract

A method based on equal frequency resampling is proposed to suppress laser nonlinear frequency sweeping for the ultimate spatial resolution in optical frequency domain reflectometry. Estimation inaccuracy of the sweeping frequency distribution caused by the finite sampling rate in the auxiliary interferometer can [...] Read more.

A method based on equal frequency resampling is proposed to suppress laser nonlinear frequency sweeping for the ultimate spatial resolution in optical frequency domain reflectometry. Estimation inaccuracy of the sweeping frequency distribution caused by the finite sampling rate in the auxiliary interferometer can be efficiently compensated by the equal frequency resampling method. With the sweeping range of 130 nm, a 12.1 µm spatial resolution is experimentally obtained. In addition, the sampling limitation of the auxiliary interferometer-based correction is discussed. With a 200 m optical path delay in the auxiliary interferometer, a 21.3 µm spatial resolution is realised at the 191 m fibre end. By employing the proposed resampling and a drawing tower FBG array to enhance the Rayleigh backscattering, a distributed temperature sensing over a 105 m fibre with a sensing resolution of 1 cm is achieved. The measured temperature uncertainty is limited to ±0.15 °C. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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14 pages, 2080 KiB

Open AccessArticle

Performance Study of a Zirconia-Doped Fiber for Distributed Temperature Sensing by OFDR at 800 °C

by Patrick Bulot, Rémy Bernard, Monika Cieslikiewicz-Bouet, Guillaume Laffont and Marc Douay

Sensors 2021, 21(11), 3788; https://doi.org/10.3390/s21113788 - 30 May 2021

Cited by 15 | Viewed by 3702

Abstract

Optical Frequency Domain Reflectometry (OFDR) is used to make temperature distributed sensing measurements along a fiber by exploiting Rayleigh backscattering. This technique presents high spatial and high temperature resolutions on temperature ranges of several hundred of degrees Celsius. With standard telecommunications fibers, measurement [...] Read more.

Optical Frequency Domain Reflectometry (OFDR) is used to make temperature distributed sensing measurements along a fiber by exploiting Rayleigh backscattering. This technique presents high spatial and high temperature resolutions on temperature ranges of several hundred of degrees Celsius. With standard telecommunications fibers, measurement errors coming from the correlation between a high temperature Rayleigh trace and the one taken as a reference at room temperature could be present at extremely high temperatures. These correlation errors, due to low backscattering signal amplitude and unstable backscattering signal, induce temperature measurement errors. Thus, for high temperature measurement ranges and at extremely high temperatures (e.g., at 800 °C), a known solution is to use fibers with femtosecond laser inscribed nanograting. These fs-laser-insolated fibers have a high amplitude and thermally stable scattering signal, and they exhibit lower correlation errors. In this article, temperature sensing at 800 °C is reported by using an annealed zirconia-doped optical fiber with an initial 40.5-dB enhanced scattering signal. The zirconia-doped fiber presents initially OFDR losses of 2.8 dB/m and low OFDR signal drift at 800 °C. The ZrO₂-doped fiber is an alternative to nanograting-inscribed fiber to make OFDR distributed fiber sensing on several meters with gauge lengths of 1 cm at high temperatures. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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10 pages, 1844 KiB

Open AccessArticle

Monitoring of a Highly Flexible Aircraft Model Wing Using Time-Expanded Phase-Sensitive OTDR

by Miguel Soriano-Amat, David Fragas-Sánchez, Hugo F. Martins, David Vallespín-Fontcuberta, Javier Preciado-Garbayo, Sonia Martin-Lopez, Miguel Gonzalez-Herraez and María R. Fernández-Ruiz

Sensors 2021, 21(11), 3766; https://doi.org/10.3390/s21113766 - 28 May 2021

Cited by 14 | Viewed by 3567

Abstract

In recent years, the use of highly flexible wings in aerial vehicles (e.g., aircraft or drones) has been attracting increasing interest, as they are lightweight, which can improve fuel-efficiency and distinct flight performances. Continuous wing monitoring can provide valuable information to prevent fatal [...] Read more.

In recent years, the use of highly flexible wings in aerial vehicles (e.g., aircraft or drones) has been attracting increasing interest, as they are lightweight, which can improve fuel-efficiency and distinct flight performances. Continuous wing monitoring can provide valuable information to prevent fatal failures and optimize aircraft control. In this paper, we demonstrate the capabilities of a distributed optical fiber sensor based on time-expanded phase-sensitive optical time-domain reflectometry (TE-ΦOTDR) technology for structural health monitoring of highly flexible wings, including static (i.e., bend and torsion), and dynamic (e.g., vibration) structural deformation. This distributed sensing technology provides a remarkable spatial resolution of 2 cm, with detection and processing bandwidths well under the MHz, arising as a novel, highly efficient monitoring methodology for this kind of structure. Conventional optical fibers were embedded in two highly flexible specimens that represented an aircraft wing, and different bending and twisting movements were detected and quantified with high sensitivity and minimal intrusiveness. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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18 pages, 3741 KiB

Open AccessArticle

Uncertainties in Measuring Soil Moisture Content with Actively Heated Fiber-Optic Distributed Temperature Sensing

by Robert Wu, Pierrick Lamontagne-Hallé and Jeffrey M. McKenzie

Sensors 2021, 21(11), 3723; https://doi.org/10.3390/s21113723 - 27 May 2021

Cited by 9 | Viewed by 2803

Abstract

Actively heated fiber-optic distributed temperature sensing (aFO-DTS) measures soil moisture content at sub-meter intervals across kilometres of fiber-optic cable. The technology has great potential for environmental monitoring but calibration at field scales with variable soil conditions is challenging. To better understand and quantify [...] Read more.

Actively heated fiber-optic distributed temperature sensing (aFO-DTS) measures soil moisture content at sub-meter intervals across kilometres of fiber-optic cable. The technology has great potential for environmental monitoring but calibration at field scales with variable soil conditions is challenging. To better understand and quantify the errors associated with aFO-DTS soil moisture measurements, we use a parametric numerical modeling approach to evaluate different error factors for uniform soil. A thermo-hydrogeologic, unsaturated numerical model is used to simulate a 0.01 m by 0.01 m two-dimensional domain, including soil and a fiber-optic cable. Results from the model are compared to soil moisture values calculated using the commonly used T_cum calibration method for aFO-DTS. The model is found to have high accuracy between measured and observed saturations for static hydrologic conditions but shows discrepancies for more realistic settings with active recharge. We evaluate the performance of aFO-DTS soil moisture calculations for various scenarios, including varying recharge duration and heterogeneous soils. The aFO-DTS accuracy decreases as the variability in soil properties and intensity of recharge events increases. Further, we show that the burial of the fiber-optic cable within soil may adversely affect calculated results. The results demonstrate the need for careful selection of calibration data for this emerging method of measuring soil moisture content. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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15 pages, 4219 KiB

Open AccessArticle

Distributed High Temperature Monitoring of SMF under Electrical Arc Discharges Based on OFDR

by Chen Chen, Song Gao, Liang Chen and Xiaoyi Bao

Sensors 2020, 20(22), 6407; https://doi.org/10.3390/s20226407 - 10 Nov 2020

Cited by 15 | Viewed by 2377

Abstract

The distributed high temperature measurement of an optical fiber subjected to electric arc discharges based on optical frequency-domain reflectometry is experimentally demonstrated. The distributed temperature profile is attained in an open glow regime of a few milliamps with maximum detectable temperature up to [...] Read more.

The distributed high temperature measurement of an optical fiber subjected to electric arc discharges based on optical frequency-domain reflectometry is experimentally demonstrated. The distributed temperature profile is attained in an open glow regime of a few milliamps with maximum detectable temperature up to 2100 ± 20 °C. The discharge arc-induced softened length of the fiber and mechanical stress are measured and statistically analyzed in terms of the correlation of the Rayleigh spectra. The large wavelength scanning range of OFDR enables much higher accuracy for the delay time measurement with a minimum measured delay of 40 fs. The delay shift over the entire heating range for a single discharge duration is statistically calculated by using a temporal correlation method. The reliability of the thermal sensitivity coefficient as 10 pm/°C for telecom single mode fiber (SMF, @1550 nm) is quantitatively analyzed and evaluated by the correlation coefficient. Lastly, a spectral mapping method is employed in spectrum monitoring for discharge dynamic impact on the optical path length (OPL) and local Rayleigh scatter. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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Review

Jump to: Research, Other

41 pages, 33080 KiB

Open AccessReview

Scientific Applications of Distributed Acoustic Sensing: State-of-the-Art Review and Perspective

by Boris G. Gorshkov, Kivilcim Yüksel, Andrei A. Fotiadi, Marc Wuilpart, Dmitry A. Korobko, Andrey A. Zhirnov, Konstantin V. Stepanov, Artem T. Turov, Yuri A. Konstantinov and Ivan A. Lobach

Sensors 2022, 22(3), 1033; https://doi.org/10.3390/s22031033 - 28 Jan 2022

Cited by 73 | Viewed by 8717

Abstract

This work presents a detailed review of the development of distributed acoustic sensors (DAS) and their newest scientific applications. It covers most areas of human activities, such as the engineering, material, and humanitarian sciences, geophysics, culture, biology, and applied mechanics. It also provides [...] Read more.

This work presents a detailed review of the development of distributed acoustic sensors (DAS) and their newest scientific applications. It covers most areas of human activities, such as the engineering, material, and humanitarian sciences, geophysics, culture, biology, and applied mechanics. It also provides the theoretical basis for most well-known DAS techniques and unveils the features that characterize each particular group of applications. After providing a summary of research achievements, the paper develops an initial perspective of the future work and determines the most promising DAS technologies that should be improved. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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21 pages, 10655 KiB

Open AccessReview

Seismic Applications of Downhole DAS

by Ariel Lellouch and Biondo L. Biondi

Sensors 2021, 21(9), 2897; https://doi.org/10.3390/s21092897 - 21 Apr 2021

Cited by 34 | Viewed by 5620

Abstract

Distributed Acoustic Sensing (DAS) is gaining vast popularity in the industrial and academic sectors for a variety of studies. Its spatial and temporal resolution is ever helpful, but one of the primary benefits of DAS is the ability to install fibers in boreholes [...] Read more.

Distributed Acoustic Sensing (DAS) is gaining vast popularity in the industrial and academic sectors for a variety of studies. Its spatial and temporal resolution is ever helpful, but one of the primary benefits of DAS is the ability to install fibers in boreholes and record seismic signals in depth. With minimal operational disruption, a continuous sampling along the trajectory of the borehole is made possible. Such resolution is highly challenging to obtain with conventional downhole tools. This review article summarizes different seismic uses, passive and active, of downhole DAS. We emphasize current DAS limitations and potential ways to overcome them. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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29 pages, 7395 KiB

Open AccessReview

A Survey on Distributed Fibre Optic Sensor Data Modelling Techniques and Machine Learning Algorithms for Multiphase Fluid Flow Estimation

by Hasan Asy’ari Arief, Tomasz Wiktorski and Peter James Thomas

Sensors 2021, 21(8), 2801; https://doi.org/10.3390/s21082801 - 15 Apr 2021

Cited by 27 | Viewed by 5371

Abstract

Real-time monitoring of multiphase fluid flows with distributed fibre optic sensing has the potential to play a major role in industrial flow measurement applications. One such application is the optimization of hydrocarbon production to maximize short-term income, and prolong the operational lifetime of [...] Read more.

Real-time monitoring of multiphase fluid flows with distributed fibre optic sensing has the potential to play a major role in industrial flow measurement applications. One such application is the optimization of hydrocarbon production to maximize short-term income, and prolong the operational lifetime of production wells and the reservoir. While the measurement technology itself is well understood and developed, a key remaining challenge is the establishment of robust data analysis tools that are capable of providing real-time conversion of enormous data quantities into actionable process indicators. This paper provides a comprehensive technical review of the data analysis techniques for distributed fibre optic technologies, with a particular focus on characterizing fluid flow in pipes. The review encompasses classical methods, such as the speed of sound estimation and Joule-Thomson coefficient, as well as their data-driven machine learning counterparts, such as Convolutional Neural Network (CNN), Support Vector Machine (SVM), and Ensemble Kalman Filter (EnKF) algorithms. The study aims to help end-users establish reliable, robust, and accurate solutions that can be deployed in a timely and effective way, and pave the wave for future developments in the field. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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22 pages, 4603 KiB

Open AccessReview

Benefits of Spectral Property Engineering in Distributed Brillouin Fiber Sensing

by Cheng Feng and Thomas Schneider

Sensors 2021, 21(5), 1881; https://doi.org/10.3390/s21051881 - 8 Mar 2021

Cited by 8 | Viewed by 2126

Abstract

As one of the most consolidated distributed fiber sensors based on stimulated Brillouin scattering, the Brillouin optical time-domain analyzer (BOTDA) has been developed for decades. Despite the commercial availability and outstanding progresses which has been achieved, the intrinsic Lorentzian gain spectrum restricts the [...] Read more.

As one of the most consolidated distributed fiber sensors based on stimulated Brillouin scattering, the Brillouin optical time-domain analyzer (BOTDA) has been developed for decades. Despite the commercial availability and outstanding progresses which has been achieved, the intrinsic Lorentzian gain spectrum restricts the sensing performance from possible further enhancements and hence limits the field of validity of the technique. In this paper, the novel method of engineering the gain spectral properties of the Brillouin scattering and its application on static and dynamic BOTDA sensors will be reviewed. Such a spectral property engineering has not only provided improvements to BOTDA, but also might open a new way to enhance the performance of all kinds of distributed Brillouin fiber sensors. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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Other

Jump to: Research, Review

10 pages, 3105 KiB

Open AccessLetter

Distributed Sensing Network Enabled by High-Scattering MgO-Doped Optical Fibers for 3D Temperature Monitoring of Thermal Ablation in Liver Phantom

by Aidana Beisenova, Aizhan Issatayeva, Zhannat Ashikbayeva, Madina Jelbuldina, Arman Aitkulov, Vassilis Inglezakis, Wilfried Blanc, Paola Saccomandi, Carlo Molardi and Daniele Tosi

Sensors 2021, 21(3), 828; https://doi.org/10.3390/s21030828 - 27 Jan 2021

Cited by 8 | Viewed by 2748

Abstract

Thermal ablation is achieved by delivering heat directly to tissue through a minimally invasive applicator. The therapy requires a temperature control between 50–100 °C since the mortality of the tumor is directly connected with the thermal dosimetry. Existing temperature monitoring techniques have limitations [...] Read more.

Thermal ablation is achieved by delivering heat directly to tissue through a minimally invasive applicator. The therapy requires a temperature control between 50–100 °C since the mortality of the tumor is directly connected with the thermal dosimetry. Existing temperature monitoring techniques have limitations such as single-point monitoring, require costly equipment, and expose patients to X-ray radiation. Therefore, it is important to explore an alternative sensing solution, which can accurately monitor temperature over the whole ablated region. The work aims to propose a distributed fiber optic sensor as a potential candidate for this application due to the small size, high resolution, bio-compatibility, and temperature sensitivity of the optical fibers. The working principle is based on spatial multiplexing of optical fibers to achieve 3D temperature monitoring. The multiplexing is achieved by high-scattering, nanoparticle-doped fibers as sensing fibers, which are spatially separated by lower-scattering level of single-mode fibers. The setup, consisting of twelve sensing fibers, monitors tissue of 16 mm × 16 mm × 25 mm in size exposed to a gold nanoparticle-mediated microwave ablation. The results provide real-time 3D thermal maps of the whole ablated region with a high resolution. The setup allows for identification of the asymmetry in the temperature distribution over the tissue and adjustment of the applicator to follow the allowed temperature limits. Full article

(This article belongs to the Special Issue Distributed Optical Fiber Sensors: Applications and Technology)

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