Search Results (1,384)

The displacement of bridge towers is relatively large under strong wind action. Changes in tower displacement can reflect the usage status of the bridge towers. Therefore, it is necessary to conduct performance warning research on tower displacement under strong wind action. In this paper, the triple standard deviation method, multiple linear regression method, and interpolation method are used to preprocess monitoring data with skipped points and missing anomalies. An improved multi-rate data fusion method, validated using simulated datasets, was applied to correct monitoring data at bridge tower tops. The fused data were used to feed predictive models and generate structural performance alerts. Spectral analysis confirmed that the fused displacement measurements achieve high precision by effectively merging the low-frequency GPS signal with the high-frequency accelerometer signal. Structural integrity monitoring of wind-loaded bridge towers used modeling residuals as alert triggers. The efficacy of this proactive monitoring strategy has been quantitatively validated through statistical evaluation of alarm accuracy rates. Full article

This paper presents a novel dynamic modeling framework for gantry crane systems based on the cart double pendulum with dual cables (CDPD) model. The CDPD model systematically incorporates the effects of dual suspension cables, equalizer beams, and closed-chain kinematic constraints, enabling an accurate simulation of both symmetric and asymmetric lifting scenarios. Utilizing Kane’s method, the model efficiently handles redundant coordinates and holonomic constraints, resulting in a compact and numerically robust formulation. Validation results demonstrate strict energy conservation and consistency with traditional models in limiting cases. The proposed approach provides a unified and extensible foundation for the advanced analysis, control, and optimization of large-scale gantry crane operations. Full article

The corrosion of high-strength steel wires is a key factor impacting the durability and reliability of cable-stayed bridges. In this study, the corrosion pit features on a high-strength steel wire, which had been in service for 27 years, were extracted and modeled using three-dimensional point cloud data obtained through 3D surface scanning. The Otsu method was applied for image binarization, and each corrosion pit was geometrically represented as an ellipse. Key pit parameters—including length, width, depth, aspect ratio, and a defect parameter—were statistically analyzed. Results of the Kolmogorov–Smirnov (K–S) test at a 95% confidence level indicated that the directional angle component (θ) did not conform to any known probability distribution. In contrast, the pit width (b) and defect parameter (Φ) followed a generalized extreme value distribution, the aspect ratio (b/a) matched a Beta distribution, and both the pit length (a) and depth (d) were best described by a Gaussian mixture model. The obtained results provide valuable reference for assessing the stress state, in-service performance, and predicted remaining service life of operational stay cables. Full article

As power systems evolve rapidly, cables, essential for electric power transmission, demand accurate and timely fault diagnosis to ensure grid safety and stability. However, current cable fault diagnosis technologies often struggle with incomplete feature extraction from complex fault signals and inefficient parameter tuning in diagnostic models, hindering efficient and precise fault detection in modern power systems. To address these, this paper proposes a data-driven strategy for cable fault diagnosis in substation secondary circuits, enhanced by effective parameter optimization. Initially, wavelet packet decomposition is employed to finely divide collected cable fault current signals into multiple levels and bands, effectively extracting fault feature vectors. To tackle the challenge of selecting penalty and kernel parameters in Support Vector Machine (SVM) models, an improved Golden Jackal Optimization (GJO) algorithm is introduced. This algorithm simulates the predatory behavior of golden jackals in nature, enabling efficient global optimization of SVM parameters and significantly improving the classification accuracy and generalization capability of the fault diagnosis model. Simulation verification using real cable fault cases confirms that the proposed method outperforms traditional techniques in fault recognition accuracy, diagnostic speed, and robustness, proving its effectiveness and feasibility. This study offers a novel and efficient solution for cable fault diagnosis. Full article

This study aims to develop an integrated wireless monitoring system named MANTiS-32, which leverages an open-source platform to enable autonomous modular operation, high-speed large-volume data transmission via Wi-Fi, and the integration of multiple complex sensors. The MANTiS-32 system is composed of ESP32-based MANTiS-32 hubs connected to eight MPU-6050 sensors each via RS485. Four MANTiS-32 hubs transmit data to a main PC through an access point (AP), making the system suitable for real-time monitoring of modal information necessary for structural performance evaluation. The fundamental performance of the developed MANTiS-32 system was validated to demonstrate its effectiveness. The evaluation included assessments of acceleration and frequency response measurement performance, wireless communication capabilities, and real-time data acquisition between the MANTiS-32 hub and the eight connected MPU-6050 sensors. To assess the feasibility of using MANTiS-32 for performance monitoring, a flexible model cable-stayed bridge, representing a mid- to long-span bridge, was designed. The system’s ability to perform real-time monitoring of the dynamic characteristics of the bridge model was confirmed. A total of 26 MPU-6050 sensors were distributed across four MANTiS-32 hubs, and real-time data acquisition was successfully achieved through an AP (ipTIME A3004T) without any bottleneck or synchronization issues between the hubs. Vibration data collected from the model bridge were analyzed in real time to extract dynamic characteristics, such as natural frequencies, mode shapes, and damping ratios. The extracted dynamic characteristics showed a measurement error of less than approximately 1.6%, validating the high-precision performance of the MANTiS-32 wireless monitoring system for real-time structural performance evaluation. Full article

A cable-driven hybrid mobile robot is a kind of robot consisting of two modules connected in series, which uses multiple parallel cables to drive the moving platforms. Cable-driven robots benefit from a large workspace, low inertia, excellent dynamic performance due to the lightweight and high extensibility of cables, making them ideal for a wide range of applications, such as sports cameras, large radio telescopes, and planetary exploration. Considering the fundamental dynamic constraint imposed by the unilateral constraint of cables, the workspace and dynamic modeling for cable-driven robots require specialized study. In this paper, a novel cable-driven hybrid robot, which has two motion patterns, is designed, and an arc intersection method for analyzing workspace is applied to solve the robot workspace of two motion patterns. Based on the workspace analysis, a dynamic model for the cable-driven hybrid robot is established, laying the foundation for subsequent trajectory planning. Simulation results in MATLAB R2021a demonstrate that the cable-driven hybrid robot has a large workspace in both motion patterns and is capable of meeting various motion requirements, indicating promising application potential. Full article

Cable force distribution in cable-stayed bridges critically impacts structural safety and efficiency, yet traditional optimization methods struggle with unconventional designs due to nonlinear mechanics and computational inefficiency. This study proposes a hybrid approach combining Response Surface Methodology (RSM) and Multi-Objective Particle Swarm Optimization (MOPSO) to overcome these challenges. RSM constructs surrogate models for strain energy and mid-span displacement, reducing reliance on finite element analysis, while MOPSO optimizes Pareto solution sets for rapid cable force adjustment. Validated through an engineering case, the method reduces the main girder’s max bending moment by 8.7%, mid-span displacement by 31.2%, and strain energy by 7.1%, improving stiffness and mitigating stress concentrations. The response surface model demonstrates prediction errors of 0.35% for strain energy and 5.1% for maximum vertical mid-span deflection. By synergizing explicit modeling with intelligent algorithms, this methodology effectively resolves the longstanding efficiency–accuracy trade-off in cable force optimization for cable-stayed bridges. It achieves over 80% reduction in computational costs while enhancing critical structural performance metrics. Engineers are thereby equipped with a rapid and reliable optimization framework for geometrically complex cable-stayed bridges, delivering significant improvements in structural safety and construction feasibility. Ultimately, this approach establishes both theoretical substantiation and practical engineering benchmarks for designing non-conventional cable-stayed bridge configurations. Full article

To address the limitations of low detection efficiency and poor spatial resolution of traditional cable insulation diagnosis methods, a novel cable insulation diagnosis method based on impedance spectroscopy has been proposed. An impedance spectroscopy analysis model of the frequency response of high-voltage single-core cables under different aging conditions has been established. The initial classification of insulation condition is achieved based on the impedance phase deviation between the test cable and the reference cable. Under localized aging conditions, the impedance phase spectroscopy is more than twice as sensitive to dielectric changes as the amplitude spectroscopy. Leveraging this advantage, a multi-parameter diagnostic framework is developed that integrates key spectral features such as the first phase angle zero-crossing frequency, initial phase, and resonance peak amplitude. The proposed method enables quantitative estimation of aging severity, spatial extent, and location. This technique offers a non-invasive, high-resolution solution for advanced cable health diagnostics and provides a foundation for practical deployment of power system asset management. Full article

Addressing the stability control challenges of roadways with composite roofs in the No. 34 coal seam of Donghai Mine under high-strength mining conditions, this study employed integrated methodologies including laboratory experiments, numerical modeling, and field trials. It investigated the mechanical response characteristics of the composite roof and developed a synergistic control system, validated through industrial application. Key findings indicate significant differences in mechanical behavior and failure mechanisms between individual rock specimens and composite rock masses. A theoretical “elastic-plastic-fractured” zoning model for the composite roof was established based on the theory of surrounding rock deterioration, elucidating the mechanical mechanism where the cohesive strength of hard rock governs the load-bearing capacity of the outer shell, while the cohesive strength of soft rock controls plastic flow. The influence of in situ stress and support resistance on the evolution of the surrounding rock zone radii was quantitatively determined. The FLAC^3D strain-softening model accurately simulated the post-peak behavior of the surrounding rock. Analysis demonstrated specific inherent patterns in the magnitude, ratio, and orientation of principal stresses within the composite roof under mining influence. A high differential stress zone (σ₁/σ₃ = 6–7) formed within 20 m of the working face, accompanied by a deflection of the maximum principal stress direction by 53, triggering the expansion of a butterfly-shaped plastic zone. Based on these insights, we proposed and implemented a synergistic control system integrating high-pressure grouting, pre-stressed cables, and energy-absorbing bolts. Field tests demonstrated significant improvements: roof-to-floor convergence reduced by 48.4%, rib-to-rib convergence decreased by 39.3%, microseismic events declined by 61%, and the self-stabilization period of the surrounding rock shortened by 11%. Consequently, this research establishes a holistic “theoretical modeling-evolution diagnosis-synergistic control” solution chain, providing a validated theoretical foundation and engineering paradigm for composite roof support design. Full article

During the process of flexible aerial refueling, the flexible structure of the hose drogue assembly is affected by internal and external interference, such as docking maneuvering, deformation of the hose, attitude changes, and body vibrations, causing the hose to swing and the whipping phenomenon, which greatly limits the success rate and safety of aerial refueling operations. Based on a 2.4 m transonic wind tunnel, high-speed wind tunnel test technology of a flexible aerial refueling hose–drogue system was established to carry out experimental research on the coupling characteristics of aerodynamics and multi-body dynamics. Based on the aid of Videogrammetry Model Deformation (VMD), high-speed photography, dynamic balance, and other wind tunnel test technologies, the dynamic characteristics of the hose–drogue system in a high-speed airflow and during the approach of the receiver are obtained. Adopting flexible multi-body dynamics, a dynamic system of the tanker, hose, drogue, and receiver is modeled. The cable/beam model is based on an arbitrary Lagrange–Euler method, and the absolute node coordinate method is used to describe the deformation, movement, and length variation in the hose during both winding and unwinding. The aerodynamic forces of the tanker, receiver, hose, and drogue are modeled, reflecting the coupling influence of movement of the tanker and receiver, the deformation of the hose and drogue, and the aerodynamic forces on each other. The tests show that during the approach of the receiver (distance from 1000 mm to 20 mm), the sinking amount of the drogue increases by 31 mm; due to the offset of the receiver probe, the drogue moves sideways from the symmetric plane of the receiver. Meanwhile, the oscillation magnitude of the drogue increases (from 33 to 48 and from 48 to 80 in spanwise and longitudinal directions, respectively). The simulation results show that the shear force induced by the oscillation of the hose and the propagation velocity of both the longitudinal and shear waves are affected by the hose stiffness and Mach number. The results presented in this work can be of great reference to further increase the safety of aerial refueling. Full article

The growing demand for direct current transmission emphasizes the need for advanced insulation suitable for high-capacity, long-distance applications. Thermoplastics, especially polypropylene, offer several advantages over conventional materials like XLPE (cross-linked polyethylene) and EPR (ethylene propylene rubber), including higher thermal stability, recyclability, and reduced space charge accumulation. However, due to the inherent rigidity and limited flexibility of PP, its mechanical aging becomes a critical factor in assessing its long-term reliability as a cable insulation. In this study, mechanical aging characteristics, specifically declines in tensile strength and elongation, were selected as key indicators of insulation aging. Accelerated aging tests were conducted at 90 °C, 110 °C, and 130 °C for up to 5000 h. The experimental data were fitted to exponential models to derive aging coefficients, which formed the basis for the proposed aging model and the ACI (aging condition index). The ACI enables quantitative assessment of the current insulation condition and estimation of the remaining lifetime until a predefined threshold (e.g., ACI = 0.5) is reached. These findings contribute to the development of condition-based maintenance strategies and long-term asset management for power cables, offering practical insights for improving the reliability of future power grid systems. Full article

To address the high false alarm rate of intrusion detection systems based on distributed acoustic sensing (DAS) for power cables in complex underground environments, an innovative GRT-Transformer multimodal deep learning model is proposed. The core of this model lies in its distinctive three-branch parallel collaborative architecture: two branches employ Gramian Angular Summation Field (GASF) and Recursive Pattern (RP) algorithms to convert one-dimensional intrusion waveforms into two-dimensional images, thereby capturing rich spatial patterns and dynamic characteristics and the third branch utilizes a Gated Recurrent Unit (GRU) algorithm to directly focus on the temporal evolution features of the waveform; additionally, a Transformer component is integrated to capture the overall trend and global dependencies of the signals. Ultimately, the terminal employs a Bidirectional Long Short-Term Memory (BiLSTM) network to perform a deep fusion of the multidimensional features extracted from the three branches, enabling a comprehensive understanding of the bidirectional temporal dependencies within the data. Experimental validation demonstrates that the GRT-Transformer achieves an average recognition accuracy of 97.3% across three typical intrusion events—illegal tapping, mechanical operations, and vehicle passage—significantly reducing false alarms, surpassing traditional methods, and exhibiting strong practical potential in complex real-world scenarios. Full article

Power transmission infrastructure requires continuous inspection to prevent failures and ensure grid stability. UAV-based systems, enhanced with deep learning, have emerged as an efficient alternative to traditional, labor-intensive inspection methods. However, most existing approaches rely on separate models for cable segmentation and anomaly detection, leading to increased computational overhead and reduced reliability in real-time applications. To address these limitations, we propose PowerLine-MTYOLO, a lightweight, one-stage, multitask model designed for simultaneous power cable segmentation and broken strand detection from UAV imagery. Built upon the A-YOLOM architecture, and leveraging the YOLOv8 foundation, our model introduces four novel specialized modules—SDPM, HAD, EFR, and the Shape-Aware Wise IoU loss—that improve geometric understanding, structural consistency, and bounding-box precision. We also present the Merged Public Power Cable Dataset (MPCD), a diverse, open-source dataset tailored for multitask training and evaluation. The experimental results show that our model achieves up to +10.68% mAP@50 and +1.7% IoU compared to A-YOLOM, while also outperforming recent YOLO-based detectors in both accuracy and efficiency. These gains are achieved with a smaller model memory footprint and a similar inference speed compared to A-YOLOM. By unifying detection and segmentation into a single framework, PowerLine-MTYOLO offers a promising solution for autonomous aerial inspection and lays the groundwork for future advances in fine-structure monitoring tasks. Full article

Optimizing cable forces in cable-stayed bridges is challenging due to structural nonlinearity and the limitations of traditional methods, which often focus on isolated performance indicators. This study proposes an integrated framework combining Gaussian process regression (GPR) with an enhanced whale optimization algorithm improved by the Salp Swarm Algorithm (EWOSSA). GPR is first used to model the nonlinear relationship between cable forces and structural responses. The EWOSSA then efficiently optimizes the GPR-based model to identify optimal cable forces. A case study on a cable-stayed bridge with a 2 × 145 m main spans demonstrates the effectiveness of the proposed approach. Compared with conventional methods such as the internal-force equilibrium and zero-displacement methods, the EWOSSA-GPR framework achieves superior performance across multiple structural metrics. It ensures a more uniform cable force distribution, reduces girder displacements, and improves bending moment profiles, offering a comprehensive solution for optimal structural performance in cable-stayed bridges. Full article

The non-metallic armored optoelectronic cable (NAOC) serves as a critical component in deep-sea scientific winch systems. Due to its low density and excellent corrosion resistance, it has been widely adopted in marine exploration. However, as the operational water depth increases, the NAOC is subjected to multi-layer winding on the drum, resulting in a cumulative temperature rise that can severely impair insulation performance and compromise the safety of deep-sea operations. To address this issue, this paper conducts temperature rise experiments on NAOCs using a distributed temperature sensing test rig to investigate the effects of the number of winding layers and current amplitude on their temperature rise characteristics. Based on the experimental results, an electromagnetic thermal multi-physics field coupling simulation model is established to further examine the influence of these factors on the maximum operation time of the NAOC. Finally, a multi-variable predictive model for maximum operation time is developed, incorporating current amplitude, the number of winding layers, and ambient temperature, with a fitting accuracy of 97.92%. This research provides theoretical and technical support for ensuring the safety of deep-sea scientific operations and improving the reliability of deep-sea equipment. Full article