Search Results (206)

Accurate assessment of high-voltage cable insulation condition is essential for safe operation in complex tunnel environments. Traditional methods relying on single diagnostic indicators and fixed weighting schemes often suffer from limited accuracy and adaptability. This paper proposes a multi-parameter assessment method integrating game theory with fuzzy comprehensive evaluation. Five types of online monitoring data, namely cable surface temperature, sheath grounding current, partial discharge, tunnel humidity, and ambient temperature, are selected as diagnostic parameters. Subjective and objective weights are first derived using the analytic hierarchy process and the entropy weight method, and then optimally integrated through a game-theoretic framework. Fuzzy membership functions are applied to construct an evaluation matrix, enabling quantitative and graded assessment of insulation condition. A case study on 110 kV tunnel high-voltage land cables in Zhejiang, China, verifies the effectiveness of the approach. Results show that the proposed method more accurately reflects actual operating conditions and provides higher diagnostic precision and robustness compared with single-feature and traditional weighting methods. By combining expert knowledge with real monitoring data, this study develops a scientific and practical framework for insulation condition assessment, offering reliable support to real-time insulation monitoring and predictive maintenance applications of high-voltage power transmission systems. Full article

The utilization of treated dredged sludge as a partial replacement for natural sand and gravel in construction projects offers a promising approach to reducing the exploitation of natural resources. The conventional vacuum preloading (VP) method, while widely used for soft soil improvement, is often associated with prolonged consolidation periods and high energy consumption in its later stages. Conversely, the electroosmosis (EO) technique is effective in enhancing drainage in low-permeability soft clays but is constrained by issues including anode corrosion, high operational costs, and uneven soil reinforcement. This study presents an experimental investigation into an alternating vacuum preloading and electroosmosis method for sludge treatment based on the underlying reinforcement theory. A series of laboratory model tests was conducted using a self-made vacuum–electroosmosis alternating test device. The reinforcement efficiency was assessed through the continuous monitoring of key performance indicators during the tests, including water discharge, surface settlement, electric current, electrode corrosion, and energy consumption. Post-test evaluations of the final soil shear strength and moisture content were also performed. The test results demonstrate that the alternating vacuum–electroosmosis yielded more significant improvement than their synchronous application. Specifically, the alternating vacuum–electroosmosis increased total water discharge by 46.1%, reduced final moisture content by 20.8%, and enhanced shear strength by 35.6% relative to the synchronous mode. Furthermore, an alternating VP-EO mode was found to be particularly advantageous during the electroosmosis phases, facilitating a more stable and sustained dewatering process. In contrast, the application of vacuum preloading alone resulted in inefficient performance during the later stages, coupled with relatively high energy consumption. Full article

Gas-insulated switchgear (GIS) serves as the core equipment in substations. Its partial discharge detection requires ultrasonic sensors to be precisely aligned with millimeter-level measurement points. However, existing technologies face three major bottlenecks: the lack of surface texture on GIS makes visual feature extraction difficult; strong electromagnetic interference in substations causes image noise and loss of feature point tracking; and fixed gain control easily leads to end-effector jitter, reducing positioning accuracy. To address these challenges, this paper first employs AprilTag visual markers to define GIS measurement point features, establishing an image-based visual servo model that integrates GIS surface curvature constraints. Second, it proposes an adaptive gain algorithm based on model predictive control, dynamically adjusting gain in real-time according to visual error, electromagnetic interference intensity, and contact force feedback, balancing convergence speed and motion stability. Finally, experiments conducted on a GIS inspection platform built using a Franka Panda robotic arm demonstrate that the proposed algorithm reduces positioning errors, increases positioning speed, and improves positioning accuracy compared to fixed-gain algorithms, providing technical support for the engineering application of GIS partial discharge detection robots. Full article

Partial discharge (PD) is not only the primary manifestation of insulation deterioration in gas-insulated switchgear (GIS) but also a critical indicator of the equipment’s insulation condition. PD in GIS typically occurs at media interfaces such as the surface of the basin insulator and is characterized by high randomness and low amplitude. Conventional built-in ultra-high frequency sensors exhibit limitations in early warning and detection performance. This study proposes and demonstrates a self-sensing shielding ring embedded within the basin insulator, functioning as a novel UHF sensor. Finite-difference time-domain (FDTD) is a numerical method used to solve problems involving electromagnetic fields. Based on actual GIS structural parameters, a FDTD simulation platform is constructed and a built-in sensor is used as a control to evaluate the receiving performance of the self-sensing shielding ring for PD signals. Time-domain array simulations are conducted to investigate the influence of radial, angular and axial positions on the observed performance. The results show that the proposed shielding ring exhibits broadband and low-reflection characteristics, achieving an average S₁₁ of −6.347 dB, which is significantly lower than those of the built-in sensors (−1.270 dB and −1.274 dB). The results demonstrate that the self-sensing shielding ring enables high sensitivity and the wideband detection of partial discharge, providing a new design approach and technical foundation for online early-warning systems in GIS. Full article

High-voltage ceramic insulators are routinely exposed to short-duration overvoltages such as lightning impulses, switching surges, and partial discharges. These events occur on microsecond to millisecond timescales and can produce highly localized thermal spikes that are difficult to measure directly but may compromise long-term material integrity. This paper addresses the estimation of the internal temperature distribution immediately after a lightning impulse by solving a three-dimensional inverse heat conduction problem (IHCP). The forward problem is modeled by the transient heat diffusion equation with constant thermal diffusivity, discretized using the finite element method (FEM). Surface temperature measurements are assumed available from a 12 kV ceramic post insulator and are used to reconstruct the unknown initial condition. To address the ill-posedness of the IHCP, a spatio-temporal regularization framework is introduced and compared against spatial-only regularization. Numerical experiments investigate the effect of measurement time ($T=60$ s, 600 s, and 1800 s), mesh resolution (element sizes of 20 mm, 15 mm, and 10 mm), and measurement noise ($\sigma =1$ K and 5 K). The results show that spatio-temporal regularization significantly improves reconstruction accuracy and robustness to noise, particularly when early-time measurements are available. Moreover, it is observed that mesh refinement enhances accuracy but yields diminishing returns when measurements are delayed. These findings demonstrate the potential of spatio-temporal IHCP methods as a diagnostic tool for the condition monitoring of ceramic insulators subjected to transient electrical stresses. Full article

Rapid evolution in electrified transportation and, in general, sustainability of electrical and electronic assets is turning the traditional power supply and utilization into something more complex and less known. This transition involves increasing operating voltage and specific power, as well as various types of power supply sources, from AC sinusoidal to DC and power electronics. This revolution, beneficial for asset efficiency and resilience, does come at the cost of increased risk of failure for electrical insulation systems. Intrinsic and extrinsic aging mechanisms are not completely known under DC and power electronics, and the risk of inception of partial discharges, PD, which is the most harmful extrinsic aging factor for electrical insulation, is as high, or even higher, compared with AC. To complicate the picture, electrical and electronic components can be used at different pressure levels, such as in aerospace, and it is known that partial discharge inception voltage, PDIV, drops down, and PD magnitude increases, lowering pressure. Models to predict PDIV for surface and internal discharges, as function of pressure, have been proposed recently, but they cannot be applied straightforwardly on practical asset components where type and locations of defects generating PD is unknown. This paper wants to close this application gap. Derivation and validation of an approximate, heuristic model able to predict PDIV at various pressure levels below and above the standard atmospheric pressure, SAP, are dealt with in this paper, referring to typical asset components such as cables, motors, printed circuit-boards, PCB, and under sinusoidal AC voltage. The good capability of the model to predict PDIV and any investigated pressure, from 3 to 0.05 bar, is validated by PD measurements performed using an innovative, automatic PD analytics software able to identify the typology of defect generating PD, i.e., whether surface or internal. Full article

The discharge of dye-laden effluents remains an environmental challenge since conventional treatments remove color but not the organic load. This study systematically compared anodic oxidation (AO), electro-Fenton (EF), and photoelectro-Fenton (PEF) processes for three representative industrial dyes, such as Coriasol Red CB, Brown RBH, and Blue VT, and their ternary mixture, using boron-doped diamond (BDD) and Ti/IrO₂–SnO₂–Sb₂O₅ (MMO) anodes. Experiments were conducted in a batch reactor with 50 mM Na₂SO₄ at pH = 3.0 and current densities of 20–60 mA cm⁻². Kinetic analysis showed that AO-BDD was most effective at low pollutant loads, EF-BDD became superior at medium loads due to efficient H₂O₂ electrogeneration, and PEF-MMO dominated at higher loads by fast UVA photolysis of surface Fe(OH)²⁺ complexes. In a ternary mixture of 120 mg L⁻¹ of dyes, EF-BDD and PEF-MMO achieved >98% decolorization in 22–23 min with pseudo-first-order rate constants of 0.111–0.136 min⁻¹, whereas AO processes remained slower. COD assays revealed partial mineralization of 60–80%, with EF-BDD providing the most consistent reduction and PEF-MMO minimizing treatment time. These findings confirm that decolorization overestimates efficiency, and electrode selection must be tailored to dye structure and effluent composition. Process selection rules allow us to conclude that EF-BDD is the best robust dark option, and PEF-MMO, when UVA is available, offers practical guidelines for cost-effective electrochemical treatment of textile wastewater. Full article

Power electronic devices for AC/DC and AC/AC conversion are, nowadays, widely distributed in electrified transportation and industrial applications, which can determine significant deviation in supply voltage waveform from the AC sinusoidal and promote insulation extrinsic aging mechanisms as partial discharges (PDs). PDs are one of the most harmful processes as they are able to cause accelerated extrinsic aging of electrical insulation systems and are the cause of premature failure in electrical asset components. PD phenomenology under pulse width modulated (PWM) voltage waveforms has been dealt with in recent years, also through some IEC/IEEE standards, but less work has been performed on PD harmfulness under AC distorted waveforms containing voltage harmonics and notches. On the other hand, these voltage waveforms can often be present in electrical assets containing conventional loads and power electronics loads/drives, such as for ships or industrial installations. The purpose of this paper is to provide a contribution to this lack of knowledge, focusing on PD sensing and phenomenology. It has been shown that PD patterns can change considerably with respect to those known under sinusoidal AC when harmonic voltages and/or notches are present in the supply waveform. This can impact PD typology identification, which is based on features related to PD pattern-based physics. The adaptation of identification AI algorithms used for AC sinusoidal voltage as well as distorted AC waveforms is discussed in this paper, showing that effective identification of the type of defects generating PD, and thus of their harmfulness, can still be achieved. Full article

Electrical cable insulation, mainly composed of polymeric materials, progressively deteriorates under thermal, electrical, mechanical, and environmental stress factors. This degradation reduces dielectric strength, thermal stability, and mechanical integrity, thereby increasing susceptibility to failure modes such as partial discharges, arcing, and surface tracking—recognized precursors of fire ignition. This review consolidates current knowledge on the degradation pathways of cable insulation and their direct link to fire hazards. Emphasis is placed on mechanisms including thermal-oxidative aging, electrical treeing, surface tracking, and thermal conductivity decline, as well as the complex interactions introduced by flame-retardant additives. A bibliometric analysis of 217 publications reveals strong clustering around material degradation phenomena, while underlining underexplored areas such as ignition mechanisms, diagnostic monitoring, and system-level fire modeling. Comparative experimental findings further demonstrate how insulation aging modifies ignition thresholds, heat release rates, and smoke toxicity. By integrating perspectives from materials science, electrical engineering, and fire dynamics, this review establishes the nexus between aging mechanisms and fire hazards. Full article

Basin insulator is a critical component of gas-insulated transmission line (GIL) systems. Air gap defects and surface crack defects may form in basin insulators due to casting, installation, or transport processes. This phenomenon poses a significant threat to long-term safety and stability and may even lead to partial discharges. This study establishes a simulation model of a GIL system-incorporating insulator to systematically analyze the influence patterns of various defects on the insulation characteristics of the basin insulator. Meanwhile, an equation predicting the relationship between defect size and maximum electric field strength is derived. The research revealed the following: For short air gap defects near the conductor, increasing length reduces their impact on the surrounding electric field, with the radius having minimal effect; for long air gap defects near the conductor, increasing length amplifies their influence. Smooth air gap defects distant from the conductor show negligible variation in maximum electric field strength with increasing length, while unsmooth air gap defects exhibit more pronounced effects at shorter lengths. Under identical conditions, unsmooth air gap defects demonstrate greater influence on the electric field than smooth ones. For elliptical surface defects, variations in radius show the strongest distortion. The degree of influence from surface crack defects correlates directly with their proximity to the conductor. These findings provide critical diagnostic criteria for assessing the insulation performance of basin insulator under damaged conditions. Full article

This study evaluates the use of seawater and continental water in tailings thickening and copper flotation at laboratory scale, focusing on water reuse in mining operations in arid regions. The tailings had a mean particle size of 10 µm, with 75% < 50 µm, and a specific weight of 2.64 g/cm³. Seawater contained significantly higher ion concentrations Na⁺ 10,741 ppm, Mg²⁺ 1245 ppm, and Ca²⁺ 556 ppm compared with continental water (187, 32, and 127 ppm, respectively), which negatively affected polymer performance. Sedimentation tests showed that the anionic polymer (A3) increased settling rates by 33 times with continental water at 40 g/t, while with seawater the increase was 31 times at 60 g/t. In column thickener tests, discharge solids reached 65% with continental water and 62% with seawater, representing an annual reduction of ~17,000 m³ of recovered water when seawater is used. Consistency tests indicated that achieving slump <20% required 75% solids with continental water and 77.5% with seawater. With dewatering polymers, doses of 200 g/t achieved ~70% solids and slump values near 50%, surpassing column thickener performance. Primary flotation results showed that recirculated and filtered seawater improved copper recovery by 3–5% compared with fresh seawater, due to partial removal of interfering ions. In contrast, recirculated and filtered continental water reduced recovery by 2–4%, likely because of residual polymer effects on mineral surfaces. These findings highlight the importance of polymer selection and dosage optimization to ensure efficient water recovery and sustainable flotation performance under varying water chemistries. Full article

Internal conductive defects in composite insulators severely degrade their insulation performance and are considered concealed defects, posing a significant threat to the safe and stable operation of the power grid. Focusing on this issue, this study develops an electro-thermal multi-physical field simulation model and uses finite element analysis to investigate the electric field distribution and temperature rise characteristics. Composite insulator specimens with varying defect lengths were fabricated using the electrical erosion test. Charged tests were then conducted on these defective specimens, as well as on field-decommissioned specimens. The impact of internal conductive defects on the infrared, ultraviolet, and electric field distribution characteristics of composite insulators during operation was analyzed. The results indicate that the surface electric field of composite insulators with internal conductive defects becomes highly concentrated along the defect path, with a significant increase in electric field strength at the defect’s end. The maximum field strength migrates toward the grounded end as the defect length increases. Conductive defects lead to partial discharge and abnormal temperature rise at the defect’s end and the bending points of the composite insulator. The temperature rise predominantly manifests as “bar-form temperature rise,” with temperature rise regions correlating well with discharge areas. Conductive defects accelerate the decay-like degradation process of composite insulators through a positive feedback loop formed by the coupling of electric field distortion, Joule heating, material degradation, and discharge activity. This study identifies the key characteristics of electrical and temperature rise changes in insulators with conductive defects, reveals the deterioration evolution process and degradation mechanisms of insulators, and provides effective criteria for on-site diagnosis of conductive defects. Full article

Partial discharge (PD) is not only a critical indicator but also a major accelerating factor of insulation degradation in power transformers. Accurate identification of PD types is essential for diagnosing insulation defects and locating faults in transformers. Traditional methods based on phase-resolved partial discharge (PRPD) patterns typically rely on expert interpretation and manual feature extraction, which are increasingly being supplanted by Convolutional Neural Networks (CNNs) due to their ability to automatically extract features and deliver high classification accuracy. However, the inherent subtlety and diversity of characteristic differences among PRPD patterns, coupled with substantial noise resulting from complex electromagnetic interference, present significant hurdles to achieving accurate identification. This paper proposes a transformer partial discharge identification method based on Deep Residual Shrinkage Network (DRSN) to address these challenges. The method integrates dual-path feature extraction to capture both local and global features, incorporates a channel-domain adaptive soft-thresholding mechanism to effectively suppress noise interference, and utilizes the Focal Loss function to enhance the model’s attention to hard-to-classify samples. To validate the proposed method, given the scarcity of diverse real-world transformer PD data, an experimental platform was utilized to generate and collect PD data by artificially simulating various discharge defect models, including tip discharge, surface discharge, air-gap discharge and floating discharge. Data diversity was then enhanced through sample augmentation and noise simulation, to minimize the gap between experimental data and real-world on-site data. Experimental results demonstrate that the proposed method achieves superior partial discharge recognition accuracy and strong noise robustness on the experimental dataset. For future work, it is essential to collect more real transformer PD data to further validate and strengthen the model’s generalization capability, thereby ensuring its robust performance and applicability in practical scenarios. Full article

Massachusetts Bay in the northeastern United States is highly vulnerable to ocean acidification (OA) due to reduced buffering capacity from significant freshwater inputs. We hypothesize that acidification varies across temporal and spatial scales, with short-term variability driven by seasonal biological respiration, precipitation–evaporation balance, and river discharge, and long-term changes linked to global warming and river flux shifts. These patterns arise from complex nonlinear interactions between physical and biogeochemical processes. To investigate OA variability, we applied the Northeast Biogeochemistry and Ecosystem Model (NeBEM), a fully coupled three-dimensional physical–biogeochemical system, to Massachusetts Bay and Boston Harbor. Numerical simulation was performed for 2016. Assimilating satellite-derived sea surface temperature and sea surface height improved NeBEM’s ability to reproduce observed seasonal and spatial variability in stratification, mixing, and circulation. The model accurately simulated seasonal changes in nutrients, chlorophyll-a, dissolved oxygen, and pH. The model results suggest that nearshore areas were consistently more susceptible to OA, especially during winter and spring. Mechanistic analysis revealed contrasting processes between shallow inner and deeper outer bay waters. In the inner bay, partial pressure of pCO₂ (pCO₂) and aragonite saturation (Ω_a) were influenced by sea temperature, dissolved inorganic carbon (DIC), and total alkalinity (TA). TA variability was driven by nitrification and denitrification, while DIC was shaped by advection and net community production (NCP). In the outer bay, pCO₂ was controlled by temperature and DIC, and Ω_a was primarily determined by DIC variability. TA changes were linked to NCP and nitrification–denitrification, with DIC also influenced by air–sea gas exchange. Full article

Lightning strikes pose a significant risk during outdoor activities. The connection between conventionally used rescue blankets in alpine emergencies and the risk of lightning injury is unclear. This experimental study investigated whether rescue blankets made of aluminum-coated polyethylene terephthalate increase the likelihood of lightning injuries. High-voltage experiments of up to 2.5 MV were conducted in a controlled laboratory setting, exposing manikins to realistic lightning discharges. In a balanced test environment, two conventionally used brands were investigated. Upward leaders frequently formed on the edges along the fold lines of the foils and were significantly longer in crumpled rescue blankets (p = 0.004). When a lightning strike occurred, the thin metallic layer evaporated at the contact point without igniting the blanket or damaging the underlying plastic film. The blankets diverted surface currents and prevented current flow to the manikins, indicating potentially protective effects. The findings of this experimental study suggest that upward leaders rise from the edge areas of rescue blankets, although there is no increased risk for a direct strike. Rescue blankets may even provide partial protection against exposure to electrical charges. Full article