Search Results (97)

Turbidity currents pose significant threats to offshore seabed infrastructures, including subsea hydrocarbon production facilities and submarine communication cables. These powerful underwater flows can damage pipelines, potentially causing hydrocarbon spills that endanger local communities, the environment, and negatively impact energy production infrastructures. Therefore, a comprehensive understanding of the spatio-temporal development and destructive force of turbidity currents is essential. While numerical computation of 3D flow, sediment transport, and substrate exchange is possible, field-scale simulations are computationally intensive. In this study, we develop a simplified morphodynamic approach to model the flow properties of channelized turbidity currents and the associated trends of sediment accretion and erosion. This model is applied to the Baco–Malaylay submarine system to investigate the dynamics of a significant turbidity current event that impacted a submarine pipeline offshore the Philippines. The modeling results align with available seabed assessments and observed erosion trends of the protective rock berm. Our simplified modeling approach shows good agreement with simulations from a fully 3D numerical model, demonstrating its effectiveness in providing valuable insights while reducing computational demands. Full article

The magnetic flux leakage (MFL) method is widely acknowledged as a highly effective non-destructive evaluation (NDE) technique for detecting local damage in ferromagnetic structures such as steel wire ropes. In this study, a multi-channel MFL sensor module was developed, incorporating a purpose-designed Hall sensor array and magnetic yokes specifically shaped for steel cables. To validate the proposed damage detection method, artificial damages of varying degrees were inflicted on wire rope specimens through experimental testing. The MFL sensor module facilitated the scanning of the damaged specimens and measurement of the corresponding MFL signals. In order to improve the signal-to-noise ratio, a comprehensive set of signal processing steps, including channel equalization and normalization, was implemented. Subsequently, the detected MFL distribution surrounding wire rope defects was transformed into MFL images. These images were then analyzed and processed utilizing an object detection method, specifically employing the YOLOv9 network, which enables accurate identification and localization of defects. Furthermore, a quantitative defect detection method based on image size was introduced, which is effective for quantifying defects using the dimensions of the anchor frame. The experimental results demonstrated the effectiveness of the proposed approach in detecting and quantifying defects in steel cables, which combines deep learning-based analysis of MFL images with the non-destructive inspection of steel cables. Full article

The recognition of ice thickness on transmission lines serves as a prerequisite for controlling de-icing robots to carry out precise de-icing operations. To address the issue that existing edge computing terminals fail to meet the demands of ice thickness recognition algorithms, this paper introduces an Efficient Edge Computing Network (EECNet) specifically designed for identifying ice thickness on transmission lines. Firstly, pruning is applied to the Efficient Neural Network (ENet), removing redundant components within the encoder to decrease both the computational complexity and the number of parameters in the model. Secondly, a Dilated Asymmetric Bottleneck Module (DABM) is proposed. By integrating different types of convolutions, this module effectively strengthens the model’s capability to extract features from ice-covered transmission lines. Then, an Efficient Partial Conv Module (EPCM) is designed, introducing an adaptive partial convolution selection mechanism that innovatively combines attention mechanisms with partial convolutions. This design enhances the model’s ability to select important feature channels. The method involves segmenting ice-covered images to obtain iced regions and then calculating the ice thickness using the iced area and known cable parameters. Experimental validation on an ice-covered transmission line dataset shows that EECNet achieves a segmentation accuracy of 92.7% in terms of the Mean Intersection over Union (mIoU) and an F1-Score of 96.2%, with an ice thickness recognition error below 3.4%. Compared to ENet, the model’s parameter count is reduced by 41.7%, and the detection speed on OrangePi 5 Pro is improved by 27.3%. After INT8 quantization, the detection speed is increased by 26.3%. These results demonstrate that EECNet not only enhances the recognition speed on edge equipment but also maintains high-precision ice thickness recognition. Full article

Tethered drones—defined in this work as multirotor aerial platforms physically connected to a ground station via a cable—have emerged as a transformative subclass of Tethered Unmanned Aerial Vehicles (TUAVs), offering enhanced power autonomy, communication robustness, and safety through a physical ground connection. This review provides a comprehensive analysis of the current state of tethered drone systems technology, focusing on critical system components such as power delivery, data transmission, tether management, and modeling frameworks. Emphasis is placed on the tether multifunctional role—not only as a physical link but also as a sensor, actuator, and communication channel—impacting both hardware design and control strategies. By consolidating fragmented research across disciplines, this work offers a unified reference for the design, implementation, and advancement of TUAV systems, with tethered drones as their principal application. Full article

Ultra-high-speed integrated communication and sensing (ICS) transmission techniques are highly desired for next-generation highly reliable optical transport networks (OTNs). The inherent multiple-channel advantage of uncoupled multi-core fibers (MCFs) empowers the evolution of ICS techniques. In this paper, we demonstrate an ultra-high-speed ICS OTN system utilizing 130 Gbaud probability constellation shaping 64-ary quadrature amplitude modulation (PCS-64QAM) 1.2 Tb/s OTN transponders and polarization-based sensing technique over a field-deployed seven-core MCF cable for the first time. A real-time 267.8 Tb/s 2 × 70.76 km transmission is achieved by only utilizing C-band signals thanks to the high-performance 1.2 Tb/s OTN transponders. Moreover, the ICS system can sense environmental impacts on the MCF cable such as shaking, striking, etc., in real time. The capacity of the transmission system can also be further enhanced by using signals in the L-band. Our work demonstrates the feasibility of simultaneously achieving ultra-high-speed data transmission and the real-time sensing of environmental disturbances over a field-deployed MCF cable, which we believe is a crucial milestone for next-generation ultra-high-speed highly reliable optical transmission networks. Full article

Wireless indoor positioning systems are challenged by the reliance on densely deployed hardware and exhaustive site surveys, leading to elevated deployment and maintenance costs that limit scalability. This paper introduces a novel positioning framework that enhances the existing In-Building Wireless (IBW) infrastructure by retransmitting Global Navigation Satellite System (GNSS) signals. Pseudorange residuals extracted from raw GNSS measurements, when mapped against known cable lengths, facilitate anchor identification and precise ranging. In parallel, directional and inertial measurements are derived from the channel state information (CSI) of cellular reference signals. Building upon these observations, we develop a Hybrid Adaptive Filter-Graph Fusion (HAF-GF) algorithm for high-precision positioning, wherein the adaptive filter modulates observation noise based on Line-of-Sight (LoS) conditions, while a factor graph optimization over multiple positional constraints ensures global consistency and accelerates convergence. Ray tracing-based simulations in a complex office environment validate the efficacy of the proposed approach, demonstrating a 30% improvement in positioning accuracy and at least a threefold increase in deployment efficiency compared to conventional methods. Full article

This article presents the decision feedback equalizer (DFE), the maximum likelihood detection (MLD), and the radius-directed equalization (RDE) algorithms designed in MATLAB-R2018a to equalize the received signal in a dispersive optical link up to 120 km. DFE is essential for improving signal quality in several communication systems, including WiFi networks, cable modems, and long-term evolution (LTE) systems. Its capacity to mitigate inter-symbol interference (ISI) and rapidly adjust to channel variations renders it a flexible option for high-speed data transfer and wireless communications. Conversely, MLD is utilized in applications that require great precision and dependability, including multi-input–multi-output (MIMO) systems, satellite communications, and radar technology. The ability of MLD to optimize the probability of accurate symbol detection in complex, high-dimensional environments renders it crucial for systems where signal integrity and precision are critical. Lastly, RDE is implemented as an alternative algorithm to the CMA-based equalizer, utilizing the idea of adjusting the amplitude of the received distorted symbol so that its modulus is closer to the ideal value for that symbol. The algorithms are tested using a converged 5G mm-wave analog radio-over-fiber (A-RoF) system at 60 GHz. Their performance is measured regarding error vector magnitude (EVM) values before and after equalization for different optical fiber lengths and modulation formats (QPSK, 16-QAM, 64-QAM, and 128-QAM) and shows a clear performance improvement of the output signal. Moreover, the performance of the proposed algorithms is compared to three commonly used algorithms: the simple least mean square (LMS) algorithm, the constant modulus algorithm (CMA), and the adaptive median filtering (AMF), demonstrating superior results in both QPSK and 16-QAM and extending the transmission distance up to 120 km. DFE has a significant advantage over LMS and AMF in reducing the inter-symbol interference (ISI) in a dispersive channel by using previous decision feedback, resulting in quicker convergence and more precise equalization. MLD, on the other hand, is highly effective in improving detection accuracy by taking into account the probability of various symbol sequences achieving lower error rates and enhancing performance in advanced modulation schemes. RDE performs best for QPSK and 16-QAM constellations among all the other algorithms. Furthermore, DFE and MLD are particularly suitable for higher-order modulation formats like 64-QAM and 128-QAM, where accurate equalization and error detection are of utmost importance. The enhanced functionalities of DFE, RDE, and MLD in managing greater modulation orders and expanding transmission range highlight their efficacy in improving the performance and dependability of our system. Full article

The miniaturization of sensors and non-contact measurement techniques is currently at the forefront of smart grid development. This paper proposes a miniature voltage sensor whose size is significantly reduced while maintaining large bandwidth and high linearity. To minimize the impact of environmental factors on measurement accuracy, a differential structure is utilized to optimize the sensor. The sensor is designed with a dual-channel measurement mode for both high-frequency and power-frequency signals, addressing issues of signal refraction and reflection due to impedance mismatch. COMSOL Multiphysics 6.2 is employed to simulate the sensor’s structural design and placement. Moreover, the experimental analysis of key parameters, such as parallel resistance and capacitance, identifies the optimal parameter combination for low-voltage distribution lines and cables of 10 kV and below. Experiments show that the voltage sensor’s bandwidth ranges from 30 Hz–200 kHz when measured through a frequency response analyzer. Finally, through the measurement carried out on the overhead line and cable, we evaluate the linearity of the sensor according to the experimental data. Specifically, the nonlinear errors of the voltage measurement for the overhead line and cable are 0.62% and 0.57%, respectively. Full article

Based on FLAC3D finite element analysis and field measurements, this paper studies the synchronous excavation of the deep foundation pit and the adjacent underground channel in the 17th section of the Beijing Metro Line 10 Phase II project. Due to the very tight schedule and deadline, an underground channel has been added between the double-arch tunnel and the deep foundation pit and excavated synchronously with the deep foundation pit. The minimum distance between the two excavations is 5 m. It was found that (1) the underground channel excavation destroys the intact structure of the soil around the channel and foundation pit on a larger scale, which affects the formation of soil arch behind the retaining pile and thus increases the lateral pile displacement, and the addition of anchor cables at the north and south sides of the foundation pit is not necessary; (2) if conditions permit, it is the safest to excavate the underground channel first and then the foundation pit; (3) the primary interaction spacing between the two adjacent excavations is the same depth as that of the foundation pit, and when the spacing increases to twice the depth of the foundation pit, there is basically no interaction; (4) compared with the solid and heavy soil, the adjacent existing underground channel is like a “hollow, elastic, light” tube and more sensitive to the foundation pit excavation, whose uplift and deformation rebound could exert a force on the surrounding soil and then enlarge the lateral displacement of the retaining pile. Full article

The space-division multiplexed (SDM) transmission technique based on uncoupled multi-core fibers (MCF) shows great implementation potential due to its huge transmission capacity and compatibility with existing transceivers. In this paper, we demonstrate a real-time single-span 106 km field trial over deployed 4-core MCF cable using commercial 800 Gb/s optical transport network (OTN) transceivers. The transceivers achieved a modulation rate of 130 Gbaud with the optoelectronic multiple-chip module (OE-MCM) packaging technique, which enabled the adoption of a highly noise-tolerant probability constellation shaping a 16-array quadrature amplitude modulation (PCS-16QAM) modulation format for 800 Gb/s OTN transceivers, and could realize unrepeated long-span transmission. The 4-core 800 Gb/s transmission systems achieved a real-time transmission capacity of 256 Tb/s with fully loaded 80-wavelength channels over the C+L band. The performance of different kinds of 800 G OTN transceivers with different modulation formats under this long-span unrepeated optical transmission system is also estimated and discussed. This field trial demonstrates the feasibility of applying uncoupled MCF with 800 Gb/s OTN transceivers in unrepeated long-span transmission scenarios and promotes its field implementation in next-generation high-speed optical interconnection systems. Full article

Cross-linked polyethylene (XLPE) insulation is used in most advanced power cable technology. However, in traditional cross-linking, the conductivity of the cross-linking system sharply increases due to the presence of additives (antioxidants and cross-linked agents). Therefore, reducing the number of antioxidants to further reduce conductivity is a very promising method. The structural design of a new dual-functional antioxidant 5-allyloxy-2-hydroxyl-3-tert-butylbenzophenone (5ATB) has been established. The antioxidant behavior and grafting reaction of 5ATB after photocatalysis under ultraviolet (UV) conditions were further studied using density functional theory (DFT). The reaction potential energy information of the six reaction channels at the B3LYP/6-311+G(d,p) level were obtained. The calculation results indicated that the reaction Gibbs energy barrier of 5ATB with O₂ is approximately 0.48 eV lower than that of the polyethylene chain with O₂ to achieve an anti-oxidative effect. Furthermore, the reaction-active site of 5ATB accepting H is located on the C of CH₂ in a C=C double bond, as demonstrated by an analysis of NBO charge populations. The proposed mechanism has the potential to further expand the design concept of insulation materials for advanced future power cables. Full article

The complex resistivity (CR) measurement constitutes a practical methodology for investigating the internal structures of rocks and ores alongside their mineralogical compositions and the chemical properties of fluids. However, during complex resistivity testing, particularly at high frequencies, the leakage current caused by the distributed capacitance of the instrument’s acquisition channels reduces the measurement accuracy. Additionally, the contact impedance of the measuring devices and the electromagnetic coupling effects of the measurement cables further affect the complex resistivity test results of samples. To accurately characterize samples’ intrinsic induced polarization (IP) properties, we developed a broadband complex resistivity measurement system (1 mHz–100 kHz) for rocks and ores, comprising a complex resistivity analyzer and a sample holder, employing the four-electrode method. In this study, we establish a circuit model for the measurement system to analyze the influence of the distributed capacitance of the acquisition channels on the test results at elevated frequencies. We derive the error terms inherent in the instrument’s measurements across various circuit design configurations and propose a novel method for calculating the distributed capacitance of the instrument’s acquisition channels, the parasitic capacitance of the sampling resistor, and for calibrating data by reversing the polarity of the excitation signal. Furthermore, we investigate the effect of contact impedance within the measurement setup on test results and design two sample-testing devices. Through extensive testing on multiple circuit models and samples, the system achieves an accuracy of up to 1% within the 10 MΩ range. Its overall performance surpasses that of the Solartron 1260A impedance analyzer and traditional signal source forward connection calibration methods. This advancement holds significant implications for complex resistivity measurements and the study of rock physical properties. Full article

The production process of tubes for fiber optic cables is a complex process, where proper execution is crucial to the quality of the final product. This process has a complex state vector whose structure and coordinates dynamically change during the tube extrusion process. Small fluctuations in process parameters, such as temperature, extrusion pressure, production speed, and optical fiber tension, affect the optical attenuation of the final product. Such defects necessitate the withdrawal of the product. Due to the high number of process coordinates and the technological inability to automatically label those segments of the production process that cause anomalies in the final product, the authors used data clustering methods to create a training set that enabled the use of neural tools for anomaly detection. The system proposed in the main part of the paper includes a hybrid Long short-term memory (LSTM) network model, which is fed with data streams recorded on the tube extrusion production line. The input module, which performs preprocessing of input data, conducts multiresolution analysis of recorded process parameters, and recommends the process state’s belonging to a set of classes describing individual production anomalies to appropriate LSTM network modules. The learning process of the three–channel network allowed effective recognition of five classes of the monitored tube production process. The fit level of the proposed network model reached R2 values of ≥0.85. Full article

Peru is one of the most diverse countries from a geographical and climatic point of view, where there are three large ecosystem regions called coast, Sierra, and jungle. These characteristics result in the country having many hydrographic basins, with rivers of significant dimensions in terms of the width and length of the channel. In this sense, there is a permanent need to provide connectivity and promote trade between communities through road bridge infrastructure. Thus, Peru historically developed a road network and bridges during the Inca Empire in the Tawantinsuyu region, building a cobblestone road network and suspension bridges with rope cables made of plant fibers from vegetation called Coya-Ichu. This is how bridges in Peru have evolved to meet contemporary vehicular demands and provide structural stability and functionality throughout their useful life. This article presents the following sections: (a) an introduction to the evolution of bridges, (b) the current typology and inventory of bridges, (c) the characterization of the largest bridges, (d) a discussion on the architecture, engineering, construction, and structural health monitoring (AECSHM) of bridges in the face of climate change, earthquakes, and material degradation, and (e) conclusions. Finally, this article presents opportunities and challenges in terms of Peru’s architecture, engineering, construction, and structural health monitoring of road bridges. Special emphasis is given to the use of technologies from the era of Industry 4.0 to promote the digital construction and structural health monitoring of these infrastructures. Finally, it is concluded that the integration of technologies of sensors, the IoT (Internet of Things), AI (artificial intelligence), UAVs (Unmanned Aerial Vehicles), remote sensing, BIM (Building Information Modeling), and DfMA (Design for Manufacturing and Assembly), among others, will allow for more safe, reliable, durable, productive, cost-effective, sustainable, and resilient bridge infrastructures in Peru in the face of climate change. Full article

With the acceleration of urbanization, the development and utilization of urban underground spaces are becoming increasingly frequent, and the potential risks in the operation of urban dense cable passage may pose a major threat to the security of the urban power supply. Therefore, a risk assessment method for urban dense cable passage operation based on a fuzzy-analytic hierarchy process is proposed. Firstly, the operation risk parameters of urban dense cable channels are analyzed in detail. Secondly, the weight of each index is calculated based on the analytic hierarchy process to determine the importance of each index in the risk assessment. Then, according to the membership degree of each index, the fuzzy relationship matrix is constructed to describe the relationship between each index and the risk level, and the comprehensive risk level of the cable channel is obtained through the matrix operation. Finally, taking the actual operation of an urban dense cable channel in a certain area of the China Southern Power Grid as the research object, the safety of its operation is comprehensively evaluated, and the effectiveness of the fuzzy-analytic hierarchy process in the operation risk assessment of the urban dense cable channel is verified. Corresponding risk control measures and suggestions are proposed according to the evaluation results. Full article