Search Results (162)

To enable intelligent inspection of underground cable systems, this study presents a gecko-inspired quadruped robot that integrates multi-degree-of-freedom motion with a deep learning-based visual detection system. Inspired by the gecko’s flexible spine and leg structure, the robot exhibits strong adaptability to confined and uneven tunnel environments. The motion system is modeled using the standard Denavit–Hartenberg (D–H) method, with both forward and inverse kinematics derived analytically. A zero-impact foot trajectory is employed to achieve stable gait planning. For defect detection, the robot incorporates a binocular vision module and an enhanced YOLOv8 framework. The key improvements include a lightweight feature fusion structure (SlimNeck), a multidimensional coordinate attention (MCA) mechanism, and a refined MPDIoU loss function, which collectively improve the detection accuracy of subtle defects such as insulation aging, micro-cracks, and surface contamination. A variety of data augmentation techniques—such as brightness adjustment, Gaussian noise, and occlusion simulation—are applied to enhance robustness under complex lighting and environmental conditions. The experimental results validate the effectiveness of the proposed system in both kinematic control and vision-based defect recognition. This work demonstrates the potential of integrating bio-inspired mechanical design with intelligent visual perception to support practical, efficient cable inspection in confined underground environments. Full article

Corrosion-related failures have emerged as a critical driver of premature support bolt failures in underground mines, emphasizing the urgency of understanding the phenomenon with respect to enhancing safety in underground environments. This study investigated key factors influencing bolt degradation through extensive experimental evaluation of cable bolts in simulated underground bolt environments. Multi-stranded cable specimens were exposed to saturated clay, coal, mine water, and grout/cement environments. Water samples were collected weekly from critical packing sections and analyzed for pH, electrical conductivity, and dissolved oxygen. The mineralogy and atmospheric conditions were identified as principal corrosion factors, and clay-rich and coal matrices accelerated corrosion, linked to high ion mobility and oxygen diffusion. Secondary factors correlated context-dependently: pH was negatively associated with corrosion in mineral-packed environments, while conductivity was correlated with non-mineral matrices. Notably, multi-stranded cables exhibited higher localized galvanic corrosion in inter-strand zones, highlighting design vulnerabilities. This work provides pioneering evidence that geological conditions are primary drivers for corrosion-related failures, offering actionable guidance for corrosion mitigation strategies in mining infrastructure. 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

Unplanned dilution is a critical challenge in underground mining, directly affecting operating costs, resource recovery, stope stability and operational safety. This study presents an empirical–statistical framework that integrates the Mathews–Potvin stability graph, the Equivalent Linear Overbreak/Slough (ELOS) metric, and a site-specific linear calibration to improve dilution prediction in sublevel stoping operations. A database of more than 65 stopes from a Brazilian underground zinc mine was analyzed and classified as cable-bolted, non-cable-bolted, or self-supported. Planned dilution derived from the Potvin graph was compared with actual ELOS measured by cavity-monitoring surveys. Results show a strong correlation between cable-bolted/supported stopes (r = 0.918), whereas non-cabled/unsupported and self-supported stopes display lower correlations (r = 0.755 and 0.767). Applying a site-specific linear calibration lowered the mean absolute dilution error from 0.126 m to 0.101 m (≈20%), with the largest improvement (≈29%) occurring in self-supported stopes where the unadjusted graph is least reliable. Because the equation can be embedded in routine stability calculations, mines can obtain more realistic forecasts without abandoning established empirical workflows. Beyond geotechnical accuracy, the calibrated forecasts improve grade-control decisions, reduce unnecessary waste haulage, and extend resource life—thereby enhancing both the efficiency and the accessibility of mineral resources. This research delivers the first Brazilian case study that couples Potvin analysis with ELOS back-analysis to generate an operational calibration tool, offering a practical pathway for other sites to refine dilution estimates while retaining the simplicity of empirical design. Full article

Aging underground cables pose a threatening issue in distribution systems. Replacing all cables at once is economically unfeasible, making it crucial to prioritize replacements. Traditionally, age-based strategies have been used, but they are likely to fail to depict the real condition of cables. Insulation faults are influenced by electrical, mechanical, thermal, and chemical stresses, and partial discharges (PDs) often serve as early indicators and accelerators of insulation aging. The trends in PD activity provide valuable information about insulation condition, although they do not directly reveal the cable’s real age. Due to the absence of an established ranking methodology for such condition-based data, this paper proposes a fuzzy logic and fuzzy analytic hierarchy process (FAHP)-based cable vulnerability ranking framework that effectively manages uncertainty and expert-based conditions. The proposed framework requires only basic and readily accessible data inputs, specifically cable age, which utilities commonly maintain, and PD measurements, such as peak values and event counts, which can be acquired through cost-effective, noninvasive sensing methods. To systematically evaluate the method’s performance and robustness, particularly given the inherent uncertainties in cable age and PD characteristics, this study employs Monte Carlo simulations coupled with a Spearman correlation analysis. The effectiveness of the developed framework is demonstrated using real operational cable data from a Danish distribution network, meteorological information from the Danish Meteorological Institute (DMI), and synthetically generated PD data. The results confirm that the FAHP-based ranking approach delivers robust and consistent outcomes under uncertainty, thereby supporting utilities in making more informed and economical maintenance decisions. Full article

In response to the need for cable outer sound source localization, this paper proposes a collaborative localization method based on an improved generalized cross-correlation phase transform (GCC-PHAT) and multi-sensor fusion. By constructing a secondary cross-shaped sensor array model, employing a phase transform weighting function to suppress environmental noise, and incorporating an adaptive environmental compensation algorithm to eliminate multipath effects, a set of spatial localization equations is established. Innovatively, a dynamic weighting factor linked to the startup threshold is introduced; the Levenberg–Marquardt optimization algorithm is then used to iteratively solve the nonlinear equations to achieve preliminary localization in a single-pile coordinate system. Finally, a dynamic weighted fusion model is constructed through DBSCAN spatial clustering to determine the final sound source position. Experimental results demonstrate that this method reduces the mean square error of time delay estimation by 94.7% in a 90 dB industrial noise environment, decreases the localization error by 65.4% in multi-obstacle scenarios, and ultimately maintains localization accuracy within 3 m over a range of 100 m. This performance is significantly superior to that of traditional TDOA and SRP-PHAT methods, offering a high-precision localization solution for underground cable protection. Full article

Terrain conductivity meters (TCMs) are efficient devices for different sorts of subsurface investigations, including detecting and tracing buried utilities, such as metallic pipes and cables. However, data collected using TCMs are usually ambiguous and hard to interpret. This ambiguity originates from the complex shape of apparent conductivity anomalies, the influence of irrelevant conductive bodies, and the interference of random noise with the collected data. To overcome this ambiguity and produce more interpretable apparent conductivity maps, a three-step filtering routine is proposed and tested using different real datasets. The filtering routine begins with applying a Savitzky–Golay (SG) filter to reduce the effect of random noise. This is followed by a modified rolling ball (MRB) filter to convert the complex M-shape of the anomaly into a single trough pointing to the underground utility. Finally, a virtual resolution enhancement (VRE) filter is applied to enhance the pinpointing apex of the trough. The application of the proposed filtering routine to apparent conductivity data collected using different terrain conductivity meters over different utilities in different urban environments shows a significant improvement of the data and an effective ability to reveal masked underground utilities. The proposed triple filtering routine can be a starting point for a new generation of TCMs with a built-in operation mode for instantaneous delineation and characterization of underground utilities in real time. 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

High-voltage underground cables inevitably experience frequency-dependent electromagnetic (EM) losses, driven primarily by skin and proximity effects. These losses become more severe at higher harmonic frequencies, which are increasingly common in modern power networks. In traditional multi-segment cable designs, uninsulated conductor bundles enable large circular eddy current loops that elevate AC resistance and exacerbate both skin and proximity phenomena. This paper investigates the impact of introducing a thin insulating layer between individual conductor strings in a five-segment high-voltage cable model. Two insulation thicknesses, 75 µm and 100 µm, are examined via two-dimensional finite element (FE) harmonic analysis at 0, 50, 150, and 250 Hz. By confining eddy currents to smaller loops within each conductor, the insulating layer achieves up to a 60% reduction in AC losses compared to the baseline uninsulated model, lowering the ratio of AC to DC resistance from about 3.66 down to 1.47–1.49 at 250 Hz. The findings confirm that adding even a modest inter-strand insulation is highly effective at mitigating skin and proximity effects, with only marginal additional benefit from thicker insulation. Such designs offer improved energy efficiency and reduced thermal stress in underground cables, making them attractive for modern power distribution systems where harmonic content is pervasive. Full article

Artificial intelligence (AI)-based fault diagnosis methods have been widely studied for power grids, with most research focusing on fault interval localization rather than precise fault point identification. In cases involving long-distance transmission lines or underground cables, merely locating the fault interval is insufficient. This paper presents a novel fault diagnosis and precise localization method for power systems utilizing the Graph Sample and Aggregated (GraphSAGE) algorithm. A fault diagnosis and interval localization model are developed based on the system topology, identifying k-order adjacent nodes at both ends of the fault interval. This information is then used to construct an accurate fault point localization model. Leveraging the strong inductive learning capability of GraphSAGE, the proposed method effectively captures the impact of the fault point on surrounding nodes, enabling precise fault point localization. Experimental results demonstrate that the proposed method offers high fault diagnosis accuracy, precise localization, and robust performance. The model shows significant applicability in real-world fault scenarios, maintaining strong performance and economic value across varying network topologies and incomplete data collection. Full article

This paper investigates the influence of skin and proximity effects on power losses in segmented power cables using finite element (FE) analysis. Two-dimensional (2D) and three-dimensional (3D) FE models are developed to evaluate the AC-to-DC resistance ratio ($R_{\mathrm{AC}}/R_{\mathrm{DC}}$) in single-, three-, and five-segment cable configurations. Frequencies of 0, 50, 150, and 250 Hz are considered under an infinite lay length (parallel strands) assumption. This study reveals that 2D modeling provides nearly identical $R_{\mathrm{AC}}/R_{\mathrm{DC}}$ values to 3D, with deviations of less than 0.6% at 50 Hz when no twisting is present. This highlights the computational efficiency of 2D models for certain cable designs without compromising accuracy. Furthermore, this paper examines the mesh refinement and sub-conductor geometry (hexagonal packing) of underground cables under full compression assumption. The results underscore the viability of 2D cross-sectional simulations for multi-segment cables, ensuring accurate loss predictions while saving considerable computational resources. Full article

This paper presents a comprehensive three-dimensional (3D) finite-element (FE) study of skin and proximity losses in a five-segment, helically twisted underground power cable. Unlike conventional two-dimensional (2D) analyses—which assume parallel conductors and consequently overestimate eddy current losses—our 3D approach accurately captures the effects of varying lay lengths ($\lambda$). Simulations are performed from 0 Hz (DC) to 50 Hz, showing that while the per-unit-length DC resistance remains unaffected by twisting, the AC resistance can increase significantly depending on the pitch. At 50 Hz, the ratio of AC to DC resistance ($R_{\mathrm{AC}}$/$R_{\mathrm{DC}}$) ranges from about 1.32 for very tight twists ($\lambda =0.1\mathrm{m}$) to nearly 1.72 for gentle pitches ($\lambda =5.0\mathrm{m}$). Further analysis reveals that short lay lengths enhance magnetic field coupling, improving current distribution and partially mitigating losses. To quantify these findings, an exponential-saturation model is proposed to describe $R_{\mathrm{AC}}$/$R_{\mathrm{DC}}$ as a function of lay length, achieving excellent agreement ($R^2\approx 0.996$) with the 3D FE data. These results underscore the importance of considering full 3D geometry in cable design, offering a practical tool for optimizing both mechanical reliability and electromagnetic performance in high-voltage underground applications. Full article

Underground and submarine power cables are subjected to mechanical stress during installation and operation, which degrades the cable insulation and reduces the reliability of power transmission. Therefore, tests that can evaluate the mechanical properties of power cable insulation are very important. The purpose of this paper is to introduce an improved sampling method for the test sample, the peeling, for mechanical testing of power cable insulation and to evaluate the reliability of the method. The influence of the sampling method of the test sample on the mechanical property values was analyzed. The tensile strength and elongation of XLPE (cross-linked polyethylene) and PP (polypropylene) insulation prepared by the slice method and the peeling method were measured, and the surface of the test samples according to the sampling methods was photographed by SEM. The results show that the mechanical property of the cable insulation increased by more than 10% when the improved peeling method was used, and the precision of the peeling method was relatively better. The SEM analysis showed that the surface of the sliced test sample was rougher than the peeled test sample and was physically damaged. Therefore, the high reliability of the peeling method for mechanical testing of cable insulators was demonstrated. Full article

Close-distance coal seams are common in underground mining, and their spacing is short, which produces strong mining disturbance. In instances where the upper seam has been mined and a goaf has formed, a notable issue arises during the lower seam’s mining, characterized by substantial deformation of the roadway along the goaf. Field exploration and three-dimensional geological modeling have revealed that the fourth and sixth working faces and pillar of seam No. 5 are all under seam No. 2’s goaf, with an average distance of 16.70 m. Simultaneously, the double compression effect of the pillar, induced by the linkage rotation of key blocks of the lower and upper seams, is analyzed. The induction mechanism and path of the large deformation are expounded. It is thus proposed that the pillar’s width should be determined by gob-side entry, driving beneath the goaf, with the roof near the pillar being cut off in advance to realize the path of cutting off the compressed pillar. Through the simulation comparison of five kinds of pillar width combined with engineering practice, it has been determined that the best width is 8 m, and the abutment pressure is distributed in a double-peak saddle shape, with the result that the load-bearing ability is notably significant. Through the comparative simulation of roof-cutting, it was found that roof-cutting helps the roof to collapse near the pillar-side and decreases the vertical stress peak to 16.46 MPa, the shear stress peak to 5.93 MPa, and the J₂ peak to 7.23 × 10¹³ Pa, which further alleviates the pressure on the pillar. In the field, the haulage roadway’s roof was cut by two-way shaped-charge blasting, and the sandy mudstone (5.90 m) was successfully cut off. Concurrently, anchor cable reinforcement was implemented on the roof and two ribs of the ventilation roadway in proximity to the pillar, thereby ensuring stabilization and mitigating the mining effect. The engineering research provides a case and scheme reference for the operation of gob-side entry driving beneath close-distance goafs worldwide. Full article

Online partial discharge (PD) detection for power cables is one reliable means of monitoring their health. However, strong interference by white noise poses a major challenge in the process of collecting information on partial discharge signals. To solve the problem whereby the wavelet threshold estimation based on sample entropy falls into the local optimal and the wavelet noise reduction makes it difficult to process detailed information, we propose a partial discharge signal noise reduction method based on a combination of improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and discrete wavelet transform (DWT) with multiscale sample entropy (MSE). Firstly, the ICEEMDAN method was used to decompose the original sequence into multiple intrinsic mode components. The intrinsic mode function (IMF) components were grouped using the mutual information method, and high-frequency noise was eliminated using the kurtosis criterion. Next, an MSE model was established to optimize the wavelet threshold, and wavelet noise reduction was applied to the effective component. The ICEEMDAN-MSE-DWT method can retain effective information while achieving complete denoising, which alleviates the problem of information loss that occurs after denoising using the wavelet method. Lastly, as shown by our simulation and experimental results, the proposed method can effectively realize noise reduction for power cable partial discharge signals, thus providing an effective method. Full article