Time Domain Reflectometry Signal Research Articles

Unpaved road characterization during rainfall scenario: Electromagnetic wave and cone penetration assessment

This study aims to examine the effect of rainfall on integrity assessment on unpaved roads using electromagnetic waves and cone penetration. An unpaved road testbed is prepared with sandy soil in densely- and loosely-packed conditions. Site investigations using a time domain reflectometry (TDR), ground penetrating radar (GPR), and dynamic cone penetrometer (DCP) are performed on the testbed under before and after rainfall scenarios, and an additional laboratory compaction test using the soil samples is conducted. The results show that the spatially scaled GPR signal converted by the TDR signal can accurately estimate the interface depth. In addition, rainfall may reduce the accuracy of GPR signal polarity-based analyses for anomaly detection on unpaved roads. This study reveals that TDR, GPR, and DCP with simple laboratory compaction tests and physics-inspired effective stress-depth models can be a powerful tool for underground mapping when subjected to rainfall season.

Modeling and Simulation of Time Domain Reflectometry Signals on a Real Network for Use in Fault Classification and Location

Today, the classification and location of faults in electrical networks remains a topic of great interest. Faults are a major issue, mainly due to the time spent to detect, locate, and repair the cause of the fault. To reduce time and associated costs, automatic fault classification and location is gaining great interest. State-of-the-art techniques to classify and locate faults are mainly based on line-impedance measurements or the detection of the traveling wave produced by the event caused by the fault itself. In contrast, this paper describes the methodology for creating a database and a model for a complex distribution network. Both objectives are covered under the paradigm of the time-domain pulse reflectometry (TDR) principle. By using this technique, large distances can be monitored on a line with a single device. Thus, in this way a database is shared and created from the results of simulations of a real and complex distribution network modeled in the PSCAD™ software, which have been validated with measurements from an experimental test setup. Experimental validations have shown that the combination of the TDR technique with the modeling of a real network (including the real injector and the network coupling filter from the prototype) provides high-quality signals that are very similar and reliable to the real ones. In this sense, it is intended firstly that this model and its corresponding data will serve as a basis for further processing by any of the existing state-of-the-art techniques. And secondly, to become a valid alternative to the already well-known Test Feeders but adapted to work groups not used to the electrical world but to the environment of pure data processing.

A review of new TDR applications for measuring non-aqueous phase liquids (NAPLs) in soils

• NAPL monitoring in soils is performed by using invasive techniques. • Many studies demonstrated that TDR offers the possibility to detect NAPL in soils. • NAPL tests were conducted in different soils, under variable saturated conditions. The time domain reflectometry (TDR) technique is a geophysical method that allows, in a time-varying electric field, the determination of dielectric permittivity and electrical conductivity of a wide class of porous materials. Measurements of the volumetric water content (θ w ) in soils is the most frequent application of TDR in Soil Science and Soil Hydrology. In last four decades several studies have sought to explore potential applications of TDR. Such studies (except those conducted on θ w estimation) mainly focused on monitoring soil solute transport. In more recent times, innovative TDR approaches have also been implemented to extend current TDR fields of application to the problem of monitoring non-aqueous phase liquids (NAPLs) in variable saturated soils. NAPLs are organic compounds with low solubility in water and are characterised by a high mobility in the vadose zone. Due to their high toxicity, NAPLs constitute a severe geo-environmental problem, thus making detection and observation of such substances in soils an increasingly important issue. The present paper deals with these studies and aims to provide an up-to-date review of the main NAPL-TDR studies. To date, the literature has focused on TDR applications in three main fields: (i) NAPL monitoring in homogeneous, variable saturated soils, (ii) NAPL monitoring in layered variable saturated soils, and (iii) NAPL monitoring during soil decontamination processes. For an exhaustive and complete overview of TDR research in this field, we also recall the basic principles of TDR signal propagation, the functioning of a typical TDR device, and the dielectric mixing models that are widely used to interpret the dielectric response of NAPL-contaminated soils.

Temporal convolution network with a dual attention mechanism for φ-OTDR event classification.

We propose a hybrid model named channel attention based temporal convolutional network combined with spatial attention and bidirectional long short-term memory network (ATCN-SA-BiLSTM) for phase sensitive optical time domain reflectometry signal recognition. This hybrid model consists of three parts: ATCN, which extracts temporal features and preserves causality of time domain signals, the SA mechanism, which re-weights spatial sequences for better feature extraction, and BiLSTM, which extracts spatial relationships considering the bidirectional propagation characteristics of disturbances in space domain signals. Experimental results show that our method achieves better classification performance with an accuracy of 93.4% and zero nuisance alarm rate.

Self-Referencing TDR Dielectric Spectroscopy Using Reflection-Decoupled Analysis With a Mismatched Section

An innovative self-referencing time-domain reflectometry (TDR) dielectric spectroscopy method is introduced. The method extracts the first reflection from a mismatched section (MS) immediately before the sensing section (SS) to capture the source characteristics and effect of leading sections. A reflection-decoupled analysis (RDA) is derived to characterize the complex dielectric permittivity (CDP) in the ss. Conventional time-domain spectroscopy (TDS) offers a more cost-effective alternative to frequency-domain methods, but its accuracy may suffer from input function variation, system mismatches, and probe design restrictions. RDA with MS approach provides an efficient, robust, and flexible dielectric spectroscopy technique including its calibration, which inherits all advantages of conventional TDS while using more economic TDR device and more flexible probe design. It adopts a nonconductive and nondispersive MS to serve as a reflector for reliable reference source directly embedded in a single TDR signal. Spectral ratios between the reflection from MS and all other reflections from the SS are experimentally determined and matched to the RDA-derived values as a function of CDP. RDA is inherently independent of source function, instrument mismatch, and cable resistance. There are only four frequency-independent system parameters that can be easily calibrated once and for all using a measurement of well-known material. The method is presented in a general framework without major restrictive assumptions, which explicitly expresses all probe parameters, allowing greater flexibility in probe design (e.g., geometric impedance, probe length, and end condition). Robustness of RDA was verified by numerical and experimental investigations using eight materials of different dielectric characteristics.

Detection and Characterization of Multiple Discontinuities in Cables with Time-Domain Reflectometry and Convolutional Neural Networks.

In this paper, a convolutional neural network for the detection and characterization of impedance discontinuity points in cables is presented. The neural network analyzes time-domain reflectometry signals and produces a set of estimated discontinuity points, each of them characterized by a class describing the type of discontinuity, a position, and a value quantifying the entity of the impedance discontinuity. The neural network was trained using a great number of simulated signals, obtained with a transmission line simulator. The transmission line model used in simulations was calibrated using data obtained from stepped-frequency waveform reflectometry measurements, following a novel procedure presented in the paper. After the training process, the neural network model was tested on both simulated signals and measured signals, and its detection and accuracy performances were assessed. In experimental tests, where the discontinuity points were capacitive faults, the proposed method was able to correctly identify 100% of the discontinuity points, and to estimate their position and entity with a root-mean-squared error of 13 cm and 14 pF, respectively.

TDR-based Multiple Leak Detection System using an S-parameter Transmission Line Model for Long-Distance Pipelines

Leaks in water distribution systems should be detected to avoid economic, environmental, and social problems. Existing Bayesian Inference based time-domainreflectometry (TDR) methods for leak detection have a limitation for real applications due to the lengthy time in building sample data. As the pipeline distance becomes longer and multiple leaks must be considered in long distance pipelines, the computational time for building training data gets larger. This paper proposes a scattering-parameter-based forward model to relieve computational burden of the existing TDR methods. It was shown that the proposed model outperformed the existing RLGC-based forward model in terms of computational time. The proposed model that is combined with Bayesian inference and TDR signal modeling is validated with an experimental pipeline, leak detectors, transmission line, and TDR instrument for leak detection. In summary, the proposed method is promising for leak detection in long pipelines as well as multiple leaks.

Applicability and limitations of time domain reflectometry bridge scour monitoring system in general field conditions

A real-time and durable system for scour process monitoring with sufficient spatial precision is in pressing need for bridge safety management. In light of this, an innovative bundled time domain reflectometry sensing cable was recently proposed to enhance the time domain reflectometry technique for scour monitoring. However, current development only dealt with the construction of bundled sensing cable and the corresponding new data reduction method. Before it can be put into practical use, issues related to the effect of hydrological conditions, long-distance measurement, and actual field implementation are yet to be investigated. This study used both numerical simulations and laboratory experiments to examine the time domain reflectometry signals in response to both scour and deposition in different water-level conditions. As a result, the first guideline of waveform classification and interpretation is newly proposed to validly determine scour depth under various field conditions. Since field measurements often come with significant signal attenuation from resistance loss of long cable and dielectric and conductive loss in the sensing section, numerical simulations and a series of full-scale experiments were also conducted to assess the time domain reflectometry scour measurement range. The maximum measurement range of the latest time domain reflectometry scour sensing cable was found to be about 6 m. Within this range, the maximum error of scour estimation is within 0.2 m. Considering the new findings, a field time domain reflectometry scour monitoring system using the bundled time domain reflectometry sensing cable was designed accordingly and implemented at a bridge for the first time. The monitoring system successfully captured the scour process during a storm event and revealed some practical issues for future improvement as well.

Modeling and Monitoring of Wood Moisture Content Using Time-Domain Reflectometry

Time-domain reflectometry (TDR) can monitor the moisture content (MC) of water saturated logs stored in wet-decks where the MC exceeds the range that can be measured using traditional moisture meters (>50%). For this application to become routine, it is required that TDR monitoring of wet-decks occurs after establishment, and tools are needed that automate data collection and analysis. We developed models that predict wood MC using three-rod epoxy encased TDR probes inserted into the transverse surface of bolts (prior wet-deck studies were installed on the tangential surface). Models were developed for southern pine, sweetgum, yellow poplar, hickory, red oak, and white oak using a Campbell Scientific TDR100. For each species, at least 37 bolts were soaked for a minimum of three months and then air dried with TDR waveforms, and MC was periodically recorded. Calibrations were developed between MC and the TDR signal using nonlinear mixed effects models. Fixed effects ranged from excellent (southern pine R2 = 0.93) to poor (red oak R2 = 0.36, hickory R2 = 0.38). Independent of wood species, random effects all had a R2 greater than 0.80, which indicates that TDR detects changes in MC at the individual sample level. Use of TDR combined with a datalogger was demonstrated in an operational wet-deck that monitored changes in MC over 12 months, and in a laboratory trial where bolts were exposed to successive wet-dry cycles over 400 days. Both applications demonstrated the utility of TDR to monitor changes in wood MC in high MC environments where periodic measurement is not feasible due to operational safety concerns. Because a saturated TDR reading indicates a saturated MC, and because of the relatively accurate random effects found here, developing individual species models is not necessary for monitoring purposes. Therefore, application of TDR monitoring can be broadly applied for wet-decks, regardless of the species stored.

Dielectric Spectroscopy Using Dual Reflection Analysis of TDR Signals.

Time-domain reflectometry (TDR) has been a powerful tool for measuring soil dielectric properties. Initiating from apparent dielectric constant () measurement up until apparent and complex dielectric spectroscopies, the embedded information in the TDR signal can be extracted to inspire our understanding of the underlying dielectric behaviors. Multiple full waveform inversion techniques have been developed to extract complex dielectric permittivity (CDP) spectrum, but most of them involved prior knowledge of input function and tedious calibration. This rendered the field dielectric spectroscopy challenging and expensive to conduct. Dual reflection analysis (DRA) is proposed in this study to measure CDP spectrum from 10 MHz to 1 GHz. DRA is a simple, robust, model-free, and source-function free algorithm which requires minimal calibration effort. The theoretical framework of DRA is established and the necessary signal processing procedures are elaborated in this study. Eight materials with different dielectric characteristics are selected to evaluate DRA’s performance, by using both simulated and experimental signals. DRA is capable of measuring non-dispersive materials very well, whereas dispersive materials require the assistance of a long-time-window (LTW) extraction method to further extend the effective bandwidth. The DRA approach is suitable for field applications that can only record a limited amount of data points and in-situ dielectric spectroscopy.

Remote Monitoring of Joints Status on In-Service High-Voltage Overhead Lines

This work presents the feasibility study of an on-line monitoring technique aimed to discover unwanted variations of longitudinal impedance along the line (also named “impedance discontinuities”) and, possibly, incipient faults typically occurring on high voltage power transmission lines, like those generated by oxidated midspan joints or bolted joints usually present on such lines. In this paper, the focus is placed on the application and proper customization of a technique based on the time-domain reflectometry (TDR) technique when applied to an in-service high-voltage overhead line. An extensive set of numerical simulations are provided in order to highlight the critical points of this particular application scenario, especially those that concern the modeling of both the TDR signal injection strategy and the required high-voltage coupling devices, and to plan a measurement activity. The modeling and simulation approach followed for the study of either the overhead line or the on-line TDR system is fully detailed, discussing three main strategies. Furthermore, some measurement data that were used to characterize the specific coupling device selected for this application at high frequency—that is, a capacitive voltage transformer (CVT)—are presented and discussed too. This work sets the basic concepts underlying the implementation of an on-line remote monitoring system based on reflectometric principles for in-service lines, showing how much impact is introduced by the high-voltage coupling strategy on the amplitude of the detected reflected voltage waves (also named “voltage echoes”).

Distributed temperature sensing with unmodified coaxial cable based on random reflections in TDR signal

This paper presents a new method to utilize an unmodified coaxial cable for distributed temperature sensing. It compares the time domain reflectometry (TDR) signal before and after temperature change by cross-correlation, and the resultant time delay will indicate the region as well as the magnitude of the temperature change. The temperature change from 27 °C to 70 °C is monitored and a linear relationship between the cross-correlation value and temperature can be observed. Two-section temperature change monitoring is also demonstrated to show its distributed sensing capability. This method is more sensitive than the traditional TDR method. Compared to coaxial cable sensors based on multiple Fabry–Perot interferometers or coaxial cable Bragg gratings, the cable does not need to be modified before installation, and it is truly distributed sensing without dark zone.

Multiple Reflection Analysis of TDR Signal for Complex Dielectric Spectroscopy

Most dielectric spectroscopy techniques require careful system calibration, tedious measurement, specially designed probes, precise input source, and some even involved complicated inversion models. This paper proposed a rapid, robust, and model-free multiple reflection analysis (MRA) of time-domain reflectometry (TDR) signals to measure the complex dielectric permittivity (CDP) spectrum. The key to MRA approach is to decompose the first top reflection and the subsequent multiple reflections from TDR signal and to compare their spectral ratio (MRA ratio). This ratio was theoretically derived from the transmission line theory and found to be independent of source function and impedance mismatches in the leading sections. Based on this theoretical formulation, the CDP spectrum can be uniquely inverted from the measured MRA ratio through optimization and an iterated initial guess method. Numerical evaluations and experimental verifications had proven that MRA is a reliable algorithm for measuring CDP spectrum covering 10 MHz–1 GHz. Factors influencing the reliable frequency region were discussed and recommendations on enhancing CDP measurement was proposed for highly dispersive materials. The MRA approach enables dielectric spectroscopy to be conveniently conducted in both laboratory and field, without complicated system setup and calibration.

Low Frequency Model-Based Identification of Soft Impedance Faults in Cables

Cables are subject to local impedance faults, or soft faults, e.g., following mechanical alterations. While their occurrence can be detected, no simple procedure exists for assessing whether a fault is critical and requires intervention. Previous work has demonstrated that the amplitude of echoes generated by time-domain reflectometry (TDR) does not measure how severe such faults are, hindering attempts at introducing early warning schemes that could prevent these faults from eventually evolving into hard faults, i.e., open or short circuits. This paper introduces a model-based identification procedure that is capable of accurately inferring how severe an impedance modification along a cable is, together with its length. It has the advantage of operating at lower frequencies than other more complex identification methods, while being intrinsically stable and well defined since faults are identified and located in separate steps, without requiring nonlinear regression techniques. The proposed method is also shown to remove the typical ambiguities found in the interpretation of TDR signals by reinstating a single reflection peak in reflectograms. General feasibility conditions for the identification of impedance faults are discussed, proving that only sufficiently long faults can univocally be identified. The accuracy of the proposed method is tested against experimental results obtained for faults of increasing severity in coaxial cables, for which TDR is shown to yield accurate estimates only when testing over a bandwidth almost $10\times $ wider.

Integration of Time Domain Reflectometry in a smouldering reactor

Self-sustaining smouldering is a novel technology that has been efficiently applied for soil remediation and the treatment of waste at very high moisture content. During smouldering, combustion of an organic phase occurs within an inert porous matrix. Simultaneously, processes such as evaporation, condensation and further migration of water take place. Due to the dynamics of the smouldering, all these processes are interconnected. Water evaporation and re-condensation is one of the main mechanisms responsible for smouldering quenching. The understanding of water migration within the porous medium is crucial for the design and development of self-sustaining smouldering reaction systems. This paper introduces the first smouldering reactor performing Time Domain Reflectometry (TDR) measurements during smouldering combustion experiments, aiming to measure water content distributions within the porous matrix. An existing smouldering reactor is transformed into a coaxial transmission line designed for the propagation of electromagnetic signals. Wet artificial faeces mixed with sand were used for the tests, as its behaviour in smouldering was extensively studied. TDR signals and temperatures at different positions along the reactor were recorded simultaneously. This allows for the determination of the temporal changes of the water content distribution within the smouldering reactor. This development is the first step towards the determination of moisture content profiles during waste smouldering treatment applications.

Research of the Vibration Source Tracking in Phase-Sensitive Optical Time-Domain Reflectometry Signals Based by Image Processing Method

This paper aims to improve the source tracking efficiency of distributed vibration signals generated by phase-sensitive optical time-domain reflectometry (Φ-OTDR). Considering the two dimensions (time and length) of Φ-OTDR signals, the authors saved and processed these signals as images after particle filtering. The filtering method could save 0.1% of hard drive space without sacrificing the original features of the signals. Then, an integrated feature extraction method was proposed to further process the generated image. The method combines three individual extraction methods, namely, texture feature extraction, shape feature extraction and intrinsic feature extraction. Subsequently, the signal of each frame image was recognized to track the vibration source. To verify the effect of the proposed method, several experiments were carried out to compare it with popular and traditional approaches. The results show that: Hard drive space is greatly conserved by saving the distributed vibration signals as images; the proposed particle filter is a desirable way to screen the vibration signals for monitoring; the integrated feature extraction outperforms the individual extraction methods for texture features, shape features and intrinsic features; the proposed method has a better effect than other popular integrated feature extraction methods; and, the signal source tracking method has little impact on the positioning accuracy of the vibration source. The research findings provide important insights into the source tracking of Φ-OTDR signals.

Silt fraction effects of frozen soils on frozen water content, strength, and stiffness

The strength and stiffness of soil mixtures vary with regard to the particle composition and the properties of soil mixtures that critically change when water, which is a component in soils, is frozen. The objective of this study is to evaluate silt fraction effects of frozen sand-silt mixtures on the frozen water content, shear strength, and stiffness. The sand-silt mixtures are prepared in a shear box at a fixed relative density of 60% and a fixed degree of saturation of 15% with various silt fractions ranging from 0 to 100% in weight (Wsilt/Wsand × 100%). A time domain reflectometry (TDR) probe, bender elements, and thermocouple are installed in the shear box, and the direct shear apparatus is placed in the freezing chamber. After the sand-silt mixtures are frozen at −5 °C, the direct shear tests are conducted. The TDR signals and shear waves are monitored before and after the freezing phases for the estimation of the volumetric water content and stiffness, respectively. Test results show that the void ratio, volumetric frozen water content, shear strength, and shear wave velocity are at a minimum near a silt fraction of 30%. As the relationships between the volumetric frozen water content and peak shear strength, as well as between the volumetric frozen water content and shear wave velocity after freezing, are linear, the peak shear strength correlates well with the shear wave velocity after freezing. Furthermore, as the residual shear strength and shear wave velocity before freezing are related to the silt fraction, the residual shear strength is bi-linearly proportional to the shear wave velocity before freezing. This study suggests that the void ratio and frozen water content of sand-silt mixtures are affected by the silt fraction. Thus, the silt fraction effects should be considered for the characterization of the strength and stiffness of frozen soils.

A time-domain reflectometry method for automated measurement of crack propagation in composites during mode I DCB testing under cold, hot, and hot/wet conditions

This article describes an automated method for the measurement of crack initiation and propagation in composite materials during modeI double cantilever beam (DCB) testing under different environmental conditions. The method uses the time-domain reflectometry (TDR)-DCB system, which transmits a high-frequency pulse through a transmission line integrated within the composite test coupon and measures impedance discontinuities generated due to the presence of a crack. Using this system, real-time crack propagation in the specimen can be monitored, and the critical fracture toughness parameters ( GIC) can be calculated in a variety of environmental conditions. TDR-DCB test method was used for the measurement of GIC for dry and wet (water-saturated) DCB samples made from E-glass fiber/vinyl ester composites under dry conditions (room temperature (RT) at 94°C) and wet conditions (RT at 60°C). For all test conditions, TDR signals showed that crack initiation and propagation was the dominant mechanism in identifying impedance changes in the material. Changes in dielectric properties of the specimen due to the test conditions, whether from water uptake, temperature, or a combination of the two, did not significantly affect signal quality.

Interpreting TDR Signal Propagation through Soils with Distinct Layers of Nonaqueous‐Phase Liquid and Water Content

Core Ideas The TDR response in the presence of NAPL transport was investigated in a homogeneous soil. The experimental framework was designed to simulate sharp NAPL fronts that moved in the soil. The TDR waveforms were analyzed to deduce the influence of NAPLs on TDR signal propagation. A general procedure to determine the location of an NAPL‐contaminated front was developed. Several studies have demonstrated that time‐domain reflectometry (TDR) has an enormous potential to detect and monitor nonaqueous‐phase liquids (NAPLs) in uniformly contaminated soils with reference to different‐textured soils and under different saturation conditions. Few attempts have been proposed to describe NAPL distribution by using TDR when a contaminated front propagates through a soil. In this study, the TDR response in the presence of NAPL‐contaminant transport processes was investigated in a homogeneous soil under confined conditions with a series of laboratory‐controlled tests. The laboratory procedure involved measurements of dielectric permittivity (εb) and electrical conductivity (ECb) and the acquisition of the reflected TDR waveforms. The experimental framework was designed to simulate sharp NAPL fronts that moved in the soil columns and generated zones of contrasting permittivity. During the experiments, different initial conditions were assumed, as well as different degrees of contamination, by varying the volumetric water (θw) and NAPL (θNAPL) contents. The acquired TDR waveforms were systematically analyzed to deduce the influence of NAPLs on TDR signal propagation. A general procedure to determine the location of an NAPL‐contaminated front within a soil column was developed. Equipment calibration, measurement accuracy, and error sources were investigated in relation to the experimental procedure setup and the column preparation conditions. The results show that there may be some difficulties when interpreting TDR signals to locate the NAPL front for two main reasons: first, the expected additional reflection at the interface is not always distinguishable; second, there may be problems even locating both the first peak and the reflection point at the end of the TDR probe, especially when the signal shifts from a low to a high impedance layer. The suggested methodology provides a tool to overcome such intrinsic difficulties in NAPL front detection during the propagation of the contaminant.

Shape of Time Domain Reflectometry Signals during the Passing of Wetting Fronts

Core Ideas Precise wetting front arrival times can be determined from local TDR readings. Wetting shock fronts due to preferential flow are sharp. This approach uses the control volume with two‐rod TDR probes as the longitudinal axis. Estimates of preferential flow rates follow from this approach. Viscous flow theory expects sharp wetting shock fronts during infiltration in permeable media, but time domain reflectometry (TDR) measurements, using horizontally installed two‐rod probes, reveal concave and convex increases at the early and late stages during the passing of the front, i.e., the TDR signals are S‐shaped. Wetting front dispersal was initially considered as the cause, due to variations in the flow path lengths at the profile scale. However, later studies favored processes that are closer to the scale of the TDR control volume. In this study, an approach was developed that quantifies the shape of TDR signals exclusively with local features. It improves the determination of the arrival time of a wetting shock front at the depth of a TDR probe, and it ultimately supports the notion of sharp wetting shock fronts at the scale of the probe's length that evolve during preferential infiltration.