Search Results (126)

Soil moisture content plays a crucial role in precision agriculture and geological hazard monitoring, driving the need for stable, reliable, and high-precision sensors. Capacitive soil moisture sensors based on Frequency Domain Reflectometry (FDR) are widely adopted due to their favorable measurement performance, yet their accuracy is highly susceptible to environmental interferences such as temperature, salinity (electrical conductivity), and soil type. This paper systematically reviews current calibration strategies addressing these three factors, classifying them into hardware-based compensation and software-based calibration (including conventional mathematical and machine learning models). Furthermore, it critically analyzes the trade-offs of these approaches in terms of robustness, scalability, and field applicability. To break through current technical limitations, this review argues that future research must prioritize the physical decoupling of multi-parameter interferences under extreme conditions. Additionally, to overcome the generalization crisis of current data-driven models, adaptive strategies utilizing techniques like transfer learning are essential. Finally, implementing Edge-AI on resource-constrained hardware is crucial for achieving calibration-free or real-time online calibration strategies, ensuring long-term measurement accuracy. Full article

To address the polarization fading noise in coherent detection phase-sensitive optical time-domain reflectometry (Φ-OTDR) for distributed low-frequency vibration sensing, a Φ-OTDR sensing scheme integrating polarization diversity reception and the variational mode decomposition (VMD) algorithm is proposed. The mechanism of polarization fading induced by fiber birefringence and external perturbations is systematically analyzed. A signal–noise mathematical model for polarization diversity reception is established, and the adaptive decomposition capability of the VMD algorithm for non-stationary phase signals is elaborated. This scheme can accurately separate the additional noise introduced by polarization diversity reception from the target low-frequency vibration signals. Experimental results demonstrate that, compared with the single-path detection scheme, the proposed method eliminates the amplitude attenuation of beat frequency signals caused by polarization mismatch at the optical path level. Meanwhile, it effectively suppresses both the additional noise introduced by polarization diversity and the low-frequency phase drift resulting from unstable laser frequency. It achieves precise phase restoration of vibration signals excited at 50 Hz under three typical sensing distances of 5 km, 10 km, and 30 km. Additionally, it successfully restores low-frequency vibration signals as low as 0.6 Hz at the sensing distance of 30 km. Full article

We propose and experimentally validate an automatic urban water leakage detection architecture that leverages dark fiber links already deployed in telecommunication networks in underground conduits in the vicinity of water pipelines. The sensing stage relies on a differential-phase coherent optical time-domain reflectometry interrogator enhanced with optical pulse compression to improve sensitivity. Building on this vibration acquisition stage, automatic leakage detection algorithms are implemented by searching for leak-induced activity in the frequency domain, which is well suited to revealing leakage-related features. After acquiring a baseline calibration to characterize normal-condition vibrations at each sensing position, leakage candidates are identified by comparing distribution-based metrics computed over multiple measurements against the corresponding baseline statistics. Two automatic leakage detection strategies are developed. First, low-complexity feature-based metrics are implemented, enabling continuous monitoring with minimal computational requirements. Second, an autoencoder-based anomaly detection technique is introduced, which also relies on location-specific normal-condition calibration but reduces the dependence on prior knowledge of the expected leakage vibration signatures. A real-world field trial on an urban network demonstrates reliable detection and localization using controlled leak events generated in the field, with measurements performed over a 17 km sensing fiber and an effective spatial resolution of 2.6 m. Benchmarking against a commercial punctual electro-acoustic leak detector yields consistent trends. Overall, the proposed system could complement existing technologies by enabling automated, continuous city-scale monitoring over already deployed dark fiber infrastructure. Full article

Fiber-optic shape sensing enables real-time monitoring of structural deformation across a wide range of applications. For large-scale structures, Brillouin-based distributed sensing, typically implemented through Brillouin Optical Time Domain Analysis (BOTDA), offers an extended range for quasi-static measurements, albeit its limited spatial resolution degrades reconstruction accuracy. This study addresses this fundamental limitation through the introduction of a novel error compensation algorithm, particularly suited for a Brillouin-based shape sensing system, yet agnostic with respect to the sensing technology. The method leverages both the initial and final points of the sensing path, performing both forward and backward reconstructions and fusing the two trajectories by testing several polynomial and exponential weighting strategies. The algorithm is experimentally validated on a 28.91 m four-core shape sensing fiber cable (length = L), interrogated through BOTDA operating at 50 cm spatial resolution, and reconstructed through the Frenet–Serret frame formulation. Calibration procedures include radial-offset tuning and segment alignment via a hotspot reference. A non-trivial S-shaped geometry is adopted as a case study, specifically addressing curvature discontinuities arising from mixed straight and curved segments. Reconstruction accuracy is quantified through a Euclidean-distance-based Figure of Merit (FOMs). The cubic weighting strategy demonstrates improvements exceeding 86% in all FOMs compared to classical methods without compensation. Specifically, it achieves an RMSE of 0.145 m (0.50% of L), a MAE of 0.109 m (0.38% of L), and a maximum error of 0.341 m (1.18% of L). Remarkably, these percentage errors are of the same order of magnitude as those reported in the literature for Fiber Bragg Grating (FBG) and Optical Frequency Domain Reflectometry (OFDR) systems, indicating that the proposed compensation strategy enables BOTDA-based shape sensing to achieve comparable reconstruction accuracy despite its lower spatial resolution. Full article

Reflectometry-based sensing systems are widely used in industrial monitoring to assess the condition of distributed assets such as cables and transmission lines. In practical sensing environments, however, correlation-based interpretation can become unreliable because of bilinear interference, dispersive propagation, and excitation mismatch, often producing artifact-related responses that lead to unnecessary inspections and reduced decision reliability. This paper proposes a temporal-consistency-based reliability enhancement framework for correlation-driven time–frequency domain reflectometry (TFDR). Instead of replacing the conventional reflectometry pipeline, the proposed method introduces a reliability-estimation layer that evaluates the trustworthiness of correlation responses and suppresses temporally inconsistent artifacts. Multiple complementary descriptors extracted from the reflected signal are jointly analyzed to determine whether a correlation response is propagation-consistent or more likely to arise from non-physical artifacts. Temporal consistency is modeled using a bidirectional long short-term memory (BiLSTM) architecture that captures long-range dependencies along the propagation sequence. Experimental results obtained from cable reflectometry measurements under varying impedance conditions show that the proposed framework effectively suppresses artifact-related correlation responses while preserving physically meaningful reflections required for fault localization. Additional cross-excitation evaluation provides preliminary evidence that the learned temporal-consistency criterion is not tightly coupled to a single excitation waveform. Because the proposed framework operates as a post-processing reliability layer, it can be integrated into existing reflectometry-based monitoring systems without the modification of the sensing hardware or excitation scheme. Full article

This work demonstrates the potential of fiber optic sensors for measuring thermal effects in lithium-ion batteries, using a fiber optic measurement method of Optical Frequency Domain Reflectometry (OFDR). The innovative application of fiber sensors allows for spatially resolved temperature measurement, particularly emphasizing the importance of monitoring not just the exterior but also the internal conditions within battery cells. Utilizing inert glass fibers as sensors, which exhibit minimal sensitivity to electric fields, opens up new pathways for their implementation in a wide range of applications, such as battery monitoring. The sensors used in this work provide real-time information along the entire length of the fiber. It is shown that using the herein presented novel sensors in a temperature range of 0–$80°\mathrm{C}$ reveals a linear, high-sensitivity thermal measurement characteristic with a local resolution of a few centimeters. Furthermore, this study presents preliminary findings on the potential application of fiber optic sensors in lithium-ion battery (LIB) cells, demonstrating that the steps required for battery integration do not impose any restrictive effects on thermal measurements. Full article

We demonstrate a distributed acoustic sensing (DAS) system based on phase-sensitive optical time-domain reflectometry (Φ-OTDR) that employs I/Q demodulation and heterodyne detection. The proposed DAS system utilizes a 90° optical hybrid to obtain in-phase (I) and quadrature (Q) signals. By applying undersampling theory, the system significantly reduces the required analog-to-digital sampling rate. In an experimental demonstration, a 200 MHz heterodyne beat signal is successfully recovered at a sampling rate of 110 MSa/s without any loss of phase information. The system achieves a spatial resolution of 10 m, a signal-to-noise ratio of approximately 63.54 dB at a demodulation frequency of 200 Hz, and a background noise level of −52.27 dB·rad2/Hz. In addition, an amplitude-based analysis of the I/Q data is used to locate vibration events and estimate their effective length, so that an adaptive differential gauge length can be chosen to suppress common-phase fluctuations and restrict phase demodulation to a short fiber segment. This approach effectively reduces data throughput and system complexity while maintaining high sensitivity and resolution, illustrating the potential for more efficient real-time DAS implementations. Full article

Understanding hydrological, agricultural, and environmental processes in soils relies on accurately measuring volumetric water content (θ), matric potential (h), and hydraulic conductivity (K). These parameters are fundamental for quantifying plant-available water, optimizing irrigation scheduling in precision agriculture, modeling watershed responses, and studying the impacts of climate change in complex ecosystems. Among these parameters, θ is truly indispensable, as it represents the primary indicator of the water status of soils and a prerequisite for interpreting the other hydraulic variables. In recent years, capacitive sensors have become one of the most widely adopted technologies for θ estimation, owing to their favorable balance between accuracy, robustness, and affordability. These sensors infer soil moisture by measuring dielectric permittivity of soils, which is strongly governed by water content, making them particularly suitable for distributed monitoring and IoT-based environmental applications. The present study aimed to develop a low-cost capacitive sensor for θ estimation. This sensor can be made using 3D printing technology combined with conductive, nickel-based paint, which (once applied on the 3D-printed guides) forms the capacitive electrode. The capacitive component operates at an operational frequency of 60 MHz. The system was subjected to a rigorous testing protocol, including calibration and validation phases under laboratory conditions using three soils of different textures. Its performance was specifically compared with the time-domain reflectometry (TDR) technique, which is widely recognized in Soil Physics and Soil Hydrology as the reference method for θ estimation due to its reliability and accuracy. These tests confirmed the effective performance of the proposed sensor, which overall exhibited good reliability within the selected validation range, corresponding to a θ range of 0 to 0.40 cm³/cm³. Full article

Spatial resolution is a critical parameter for optical frequency domain reflectometry (OFDR). Phase-sensitive OFDR (Φ-OFDR) measures strain by detecting phase variations between adjacent sampling points, having the potential to achieve the theoretical limitation of spatial resolution. However, the results of Φ-OFDR suffer from large fluctuations due to multiple types of noise, including coherent fading and system noise. This work presents an OFDR-based strain sensing method that combines phase demodulation with cross-correlation analysis to achieve high spatial resolution. In the phase demodulation, the frequency-shift averaging (FSAV) and rotating vector summation (RVS) algorithms are first employed to suppress coherent fading noise and achieve accurate strain localization. Then the cross-correlation approach with an adaptive window is proposed. Guided by the accurate strain boundary obtained from phase demodulation, the length and position of the cross-correlation window are automatically adjusted to fit for continuous and uniform strain regions. As a result, an accurate and complete strain distribution along the entire fiber is finally obtained. The experimental results show that, within a strain range of 100–700 με, the method achieves a spatial resolution of 0.27 mm for the strain boundary, with a root-mean-square error approaching 0.94%. The processing time reaches approximately 0.035 s, with a demodulation length of 1.6 m. The proposed approach offers precise spatial localization of the strain boundary and stable strain measurement, demonstrating its potential for high-resolution OFDR-based sensing applications. Full article

The artificial ground freezing (AGF) technique is widely used in the construction of subway cross passages due to its advantages of good water sealing, strong adaptability, and minimal environmental impact. However, groundwater seepage adversely affects the formation of the frozen wall. The functional relationship between the content of unfrozen water and the temperature in saturated sandy gravel was obtained using frequency domain reflectometry (FDR). Based on the theories of heat transfer and seepage in porous media, a coupled hydrothermal mathematical model of saturated ground considering phase change was established. This model was verified using results from a model test and a freezing project for a subway cross passage. Building on this, the influence of seepage velocity on the formation and closure time of the frozen wall was studied, and prediction formulas for closure times under different seepage velocities were proposed. The results demonstrate the effectiveness of the VG–Clapeyron model in predicting the unfrozen water content in saturated sandy gravel. Groundwater seepage is the core factor affecting the formation of the frozen wall. As seepage velocity increases, closure times for both the cross passage and the pump room are significantly delayed, and the difference between their respective closure times increases. The upstream sidewall is the weak link in frozen wall expansion under seepage conditions. Monitoring of the temperature field in this area should be strengthened to track the formation of the frozen wall. Full article

Ice-shedding on overhead transmission lines can easily lead to jump discharge and subsequent line tripping, and effective monitoring methods are still lacking. To address this problem, this study proposes a distributed optical fiber sensing approach based on Brillouin optical time-domain reflectometry (BOTDR) for detecting ice-shedding discharge on 110 kV conductor–ground wire. The optical fibers embedded in an optical fiber composite overhead ground wire (OPGW) are used as sensing elements. Through simulated ice-shedding discharge experiments under different icing conditions, the Brillouin frequency shift (BFS) characteristics along the OPGW fiber are investigated, and the relationship between the BFS increment caused by the discharge-induced temperature rise and the discharge parameters is revealed. The experimental results show that ice-shedding discharge produces a localized temperature-rise region in the OPGW fiber, with an axial extent of 20–40 cm and a duration of 2–4 s. The maximum BFS increment due to the discharge temperature rise, Δv_Tm, is strongly dependent on the icing condition. Under conditions of no icing, light rime, and glaze ice on the conductor only, Δv_Tm remains within 5.43–7.94 MHz, whereas when both the conductor and ground wire are covered with glaze ice, Δv_Tm decreases significantly to 2.91–3.76 MHz. Further analysis indicates that, to satisfy the requirements for detecting ice-shedding discharge, the BOTDR must achieve a spatial resolution better than 0.1 m and a temporal sampling rate of no less than 5 Hz. These findings verify the feasibility of using distributed optical fiber sensing technology to detect ice-shedding discharge and provide experimental support for studies on the associated discharge mechanisms. Full article

This review summarizes recent progress and emerging trends in multiparameter optical fiber sensing, emphasizing techniques that enable the simultaneous measurement of temperature, strain, acoustic waves, pressure, and other environmental quantities within a single sensing network. Such capabilities are increasingly important for structural health monitoring, environmental surveillance, industrial diagnostics, and geophysical observation, where multiple stimuli act on the fiber simultaneously. The paper outlines the physical principles and architectures underlying these systems and focuses on strategies for compensating and decoupling cross-sensitivity among measured parameters. Special attention is devoted to advanced distributed sensing schemes based on coherent optical frequency-domain reflectometry (C-OFDR), coherent phase-sensitive time-domain reflectometry (Φ-OTDR), and Brillouin optical time-domain reflectometry (BOTDR). Their theoretical foundations, their signal-processing algorithms, and the design modifications that improve parameter discrimination and accuracy are analyzed and compared. The review also highlights the roles of polarization and mode diversity and the growing application of machine-learning techniques in the interpretation and calibration of data. Finally, current challenges and promising directions for the next generation of fiber-optic multiparameter sensors are outlined, with a view toward high-resolution, low-cost, and field-deployable solutions for real-world monitoring applications. Full article

The long-term operational stability of a fiber optic current transformer (FOCT) is critically dependent on the integrity of its internal fiber optic loop. Conventional testing methods often fall short in providing high-precision, spatially resolved diagnosis of FOCT internal fiber links. To overcome this limitation, this paper proposes a distributed sensing and testing scheme based on Optical Frequency Domain Reflectometry (OFDR). The implemented OFDR system offers a measurement range of up to several hundred meters, with a spatial resolution of 10 μm and a localization accuracy of 1 mm. Capitalizing on these capabilities, the proposed approach enables a comprehensive inspection of the FOCT sensing coil and lead fibers. At the same time, the OFDR response of various devices in the FOCT system is analyzed, while providing precise measurements of both optical loss and reflectance. In addition, the temperature stress variation of the sensing coil is measured by using the sensing characteristics of OFDR. This work provides a powerful and indispensable tool for FOCT factory testing, field fault diagnosis, and condition monitoring, contributing significantly to the safety and stability of smart grid systems. Full article

We propose a novel distributed demodulation optimization algorithm for optical frequency domain reflectometry (OFDR). This algorithm applies discrete-time analytic (DTA) signals to the Rayleigh backscattered signal (RBS) reconstruction. The DTA-RBS algorithm utilizes only positive-frequency components in the distance domain and employs a frequency-domain construction method to generate DTA-RBS, thereby improving performance without increasing the computational complexity of the OFDR demodulation algorithm. By leveraging the envelope property, DTA-RBS enhances spectral feature information and intensity while effectively suppressing high-frequency noise and spurious oscillations introduced during reconstruction, thereby maintaining a higher correlation between the reference and test data. Comprehensive experimental validation demonstrates significant performance improvements across multiple metrics. Cross-correlation intensity analysis shows that the average peak intensity of DTA-RBS reaches 0.9527, compared to 0.9096 for the conventional method. Standard deviation measurements on unstrained fiber segments demonstrate a 63% improvement. Large-strain demodulation experiments show that DTA-RBS exhibits superior strain demodulation performance and robustness, whereas the conventional method produces anomalous data points due to false peaks obscuring genuine correlation peaks. These results confirm that the DTA-RBS method provides a theoretically rigorous and practically effective approach for enhancing the sensing accuracy, stability, and robustness of OFDR in high-precision distributed measurement applications. Full article

Cable shields may develop holes when the sheath is damaged. Time–frequency domain reflectometry (TFDR) is an effective method for detecting cable defects, but it cannot directly evaluate hole sizes. To address this issue, we analyze the impact of shield hole sizes on TFDR signals. Building on this analysis, we propose an improved dual-frequency TFDR method to measure shield holes and evaluate their sizes. This method directly measures the characteristic impedances and damage ratios using dual-frequency TFDR, followed by a two-step evaluation process to determine the hole center angles and lengths based on these measurements. Simulations and experiments validate the proposed method. In laboratory-scale experiments using a scaled cable model, and considering measurement noise, the maximum relative errors for shield hole length and center angle are 11% and 5%, respectively. Full article