Search Results (26)

Transformer winding faults (TWFs) can lead to insulation breakdown, internal short circuits, and catastrophic transformer failure. Due to their low current magnitude—particularly at early stages such as inter-turn short circuits, axial or radial displacement, or winding looseness—TWFs often induce minimal impedance changes and generate fault currents that remain within normal operating thresholds. As a result, conventional protection schemes like overcurrent relays, which are tuned for high-magnitude faults, fail to detect such internal anomalies. Moreover, frequency response deviations caused by TWFs often resemble those introduced by routine phenomena such as tap changer operations, load variation, or core saturation, making accurate diagnosis difficult using traditional FRA interpretation techniques. This paper presents a novel diagnostic framework combining Discrete Wavelet Transform (DWT) and Support Vector Machine (SVM) classification to improve the detection of TWFs. The proposed system employs region-based statistical deviation labeling to enhance interpretability across five well-defined frequency bands. It is validated on five real FRA datasets obtained from operating transformers in Gauteng Province, South Africa, covering a range of MVA ratings and configurations, thereby confirming model transferability. The system supports post-processing but is lightweight enough for near real-time diagnostic use, with average execution time under 12 s per case on standard hardware. A custom graphical user interface (GUI), developed in MATLAB R2022a, automates the diagnostic workflow—including region identification, wavelet-based decomposition visualization, and PDF report generation. The complete framework is released as an open-access toolbox for transformer condition monitoring and predictive maintenance. Full article

The northeastern Tibetan Plateau (NETP) is located at the front of the northeastward expansion of the Tibetan Plateau and is a tectonically active region with complex faults and intense seismicity. In this study, based on the high-order geomagnetic field model EMM2017, the crustal magnetic anomalies and Curie point depths (CPDs) in the NETP and adjacent areas were investigated. The relationship between the magnetic anomalies, CPDs, and seismic activity was assessed. The results show that strong earthquakes occur mainly in areas where the magnetic anomalies are negative or have a strong-to-weak transition. The CPD is located at 18–42 km. In the NETP, a shallow CPD corresponds to high heat flow. In contrast, in surrounding areas, a deep CPD corresponds to low heat flow. The northeast area from Bayan Har to the Qilian orogenic belt, and the region with a deep CPD in the Qaidam Basin, record the northeastward flow of the Tibetan Plateau. High-magnitude earthquakes are associated with depth changes in the CPD and areas with a shallow CPD. The frequent seismic activity in the NETP can be attributed to the northeastward flow of the Tibetan Plateau caused by a deep heat flux. The results can be used as a reference for the prediction of strong regional earthquakes. Full article

This work uses recurrence plots (RPs) to identify nonlinearities and non-stationary conditions in wind turbines. Traditionally, recurrence plots have been applied to vibration or acoustic data; this paper applies them to magnetometer and accelerometer data to compare the sensitivity. The recurrence plots are generated by plotting points in the phase space and identifying those points where the dynamic system returns to a similar configuration, meaning that the state variables are similar to previous conditions. The state variables for the acceleration data are the position and velocity, whereas, for the magnetometer data, they are the magnitude of the magnetic field and its integral. The time series are integrated by combining the shifting principle of harmonic functions and the empirical mode decomposition. The EMD method separates the original signal into several modes, shifts them, and combines them back. The time series were obtained from an accelerometer and a magnetometer mounted in a wind turbine. The results showed that the RP presents different patterns depending on the signal; magnetometer signals identify low-frequency components, such as magnetic field anomalies, and accelerometer signals identify high-frequency components, such as bearings and gears. Full article

This study examines the three-dimensional layered air temperature variations associated with the Hualian M6.9 earthquake, which occurred on 18 September 2022, using data from the National Center for Environmental Prediction (NCEP) and extracting background information for air temperature through tidal forces. Changes in air temperature stratification revealed that near the epicenter, temperature anomalies began on 12 September and peaked on 13 September, with pronounced increases in magnitude and area. These anomalies followed a seismic thermal anomaly pattern, i.e., one with greater amplitude and a wider range near the land surface, decreasing with altitude until they dissipated, while the other exhibited high atmospheric temperature anomalies, i.e., the upper atmospheric warming exceeded that near the land surface, likely due to meteorological factors. Stable weather conditions and a low geomagnetic Kp index and Dst index during the research period supported the reliability of these findings. The deformation field recorded by InSAR reflects crustal deformation directly caused by fault slip and stress accumulation; moreover, the area with significantly higher air temperature coincides with the areas with the most concentrated deformation. Full article

One of the manifests of air-sea interactions is the change in sea level due to meteorological forcing through wind stress and atmospheric pressure. When meteorological conditions conducive to water level increase coincide with high tides during spring tides, the sea level may rise higher than expected and pose a flood risk to coastal low-lying areas. In Hong Kong, specifically when the northeast monsoon coincides with the higher spring tides in late autumn and winter, and sometimes even compounded by the storm surge brought by late-season tropical cyclones (TCs), the result may be coastal flooding or sea inundation. Aiming at forecasting such sea level anomalies on the scale of hours and days with local tide gauges using a flexible and computationally efficient method, this study adapts a data-driven method based on empirical orthogonal functions (EOF) regression of non-uniformly lagged regional wind field from ECMWF Reanalysis v5 (ERA5) to capture the effects from synoptic weather evolution patterns, excluding the effect of TCs. Local atmospheric pressure and winds are also included in the predictors of the regression model. Verification results show good performance in general. Hindcast using ECMWF forecasts as input reveals that the reduction of mean absolute error (MAE) by adding the anomaly forecast to the existing predicted astronomical tide was as high as 30% in February on average over the whole range of water levels, as well as that compared against the Delft3D forecast in a strong northeast monsoon case. The EOF method generally outperformed the persistence method in forecasting water level anomaly for a lead time of more than 6 h. The performance was even better particularly for high water levels, making it suitable to serve as a forecast reference tool for providing high water level alerts to relevant emergency response agencies to tackle the risk of coastal inundation in non-TC situations and an estimate of the anomaly contribution from the northeast monsoon under its combined effect with TC. The model is capable of improving water level forecasts up to a week ahead, despite the general decreasing model performance with increasing lead time due to less accurate input from model forecasts at a longer range. Some cases show that the model successfully predicted both positive and negative anomalies with a magnitude similar to observations up to 5 to 7 days in advance. Full article

Gravity forward modeling as a basic tool has been widely used for topography correction and 3D density inversion. The source region is usually discretized into tesseroids (i.e., spherical prisms) to consider the influence of the curvature of planets in global or large-scale problems. Traditional gravity forward modeling methods in spherical coordinates, including the Taylor expansion and Gaussian–Legendre quadrature, are all based on spatial domains, which mostly have low computational efficiency. This study proposes a high-efficiency forward modeling method of gravitational fields in the spherical harmonic domain, in which the gravity anomalies and gradient tensors can be expressed as spherical harmonic synthesis forms of spherical harmonic coefficients of 3D density distribution. A homogeneous spherical shell model is used to test its effectiveness compared with traditional spatial domain methods. It demonstrates that the computational efficiency of the proposed spherical harmonic domain method is improved by four orders of magnitude with a similar level of computational accuracy compared with the optimized 3D GLQ method. The test also shows that the computational time of the proposed method is not affected by the observation height. Finally, the proposed forward method is applied to the topography correction of the Moon. The results show that the gravity response of the topography obtained with our method is close to that of the optimized 3D GLQ method and is also consistent with previous results. Full article

Connected and automated vehicles (CAVs), integrated with sensors, cameras, and communication networks, are transforming the transportation industry and providing new opportunities for consumers to enjoy personalized and seamless experiences. The fast proliferation of connected vehicles on the road and the growing trend of autonomous driving create vast amounts of data that need to be analyzed in real time. Anomaly detection in CAVs refers to identifying any unusual or unforeseen behavior in the data generated by vehicles’ various sensors and components. Anomaly detection aims to identify any unusual behavior that might indicate a problem or a malfunction in the vehicle. To identify and detect anomalies efficiently, a method must deal with noisy data, missing data, dynamic frequency data, and low- and high-magnitude data, and it must be accurate enough to detect anomalies in a dynamic sensor streaming environment. Therefore, this paper proposes a fast and efficient hard-voting-based technique named FT-HV, comprising three fine-tuned machine learning algorithms to detect and classify anomaly behavior in CAVs for single and mixed sensory datasets. In experiments, we evaluate our approach on the benchmark Sensor Anomaly dataset that contains data from various vehicle sensors at low and high magnitudes. Further, it contains single and mixed anomaly types that are challenging to detect and identify. The results reveal that the proposed approach outperforms existing solutions for detecting single anomaly types at low magnitudes and detecting mixed anomaly types in all settings. Furthermore, this research is envisioned to help detect and identify anomalies early and efficiently promote safer and more resilient CAVs. Full article

Positive and negative magnetic anomalies occupied the total aeromagnetic (TM) map of the Harrat ad Danun area, Saudi Arabia. Reduction to the pole (RTP) maps display the range of magnetic values (−312.4 to 209.4 nT) that vary in shape, size, and magnitude. These anomalies generally follow the NNW–SSE (Red Sea axis trend), NE–SW, and NNE–SSW trends. The NNW-SSE linear negative and positive magnetic anomalies could be brought on by buried faults, shear zones, or subsurface dikes. In the central part, the position of Au and Ba mineralization was connected to this trend. It is concluded that the principal structures are represented by the NNW–SSE, NE–SW, and NNE–SSW tendencies. Based on gridded RTP magnetic data, the 2-D power spectrum was computed and revealed the frequency of the near-surface and deep magnetic components. It is believed that the depths of the shallow and deep magnetic sources are typically 80 m and 570 m, respectively. Additional negative and positive magnetic anomalies with varied amplitudes and frequencies, trending in the NNW–SSE, ENE–WSW, and NE–SW directions, are seen when the high-pass and low-pass maps are closely examined. Many faults in various directions cut into these anomalies. The occurrence of negative linear magnetic anomalies (−36.6 nT to −137.3 nT) at this depth (80 m) is also confirmed by this map. The TDR filter and the Euler deconvolution method were used to identify the horizontal variations in magnetic susceptibility as well as the source position and depth of magnetic sources. The linear clustering rings are thought to be caused by contacts or faults with depths between 1 m to 474 m that are oriented WNW–ESE, NNE–SSW, and NNW–SSE. These faults or contacts are thought to be particularly prominent in the western, eastern, southern, northern, and central zones. The majority of felsic and mafic dikes are found to be connected to subsurface structures, showing that three structural trends—WNW–ESE, NNE–SSW, and NNW–SSE—affect the studied area. This demonstrates that important features and shear zones control the majority of Saudi Arabia’s gold deposits. A negative magnetic anomaly that is centered in the area, trending NNW–SSE and crossing the NNE–SSW fault, is connected to the plotted gold and barite mineralization in the study area. This may imply that these two tendencies are responsible for mineralization. This result raises the possibility of mineralization in the NNW negative magnetic feature located in the western part of the area. The occurrence of gold and barite was significantly impacted by the NNW–SSE and NNE–SSW structural lineaments. Full article

The interactions between the geophysical processes and geodynamics of the lithosphere play a crucial role in the geologic structure of the Earth’s crust. The Bangui magnetic anomaly is a notable feature in the lithospheric structure of the Central African Republic (CAR) resulting from a complex tectonic evolution. This study reports on the coherence in the geophysical data and magnetic anomaly field analysed from a series of maps. The data used here include raster grids on free-air altimetric gravity, magnetic EMAG2 maps, geoid EGM2008 model and topographic SRTM/ETOPO1 relief. The data were processed to analyse the correspondence between the geophysical and geologic setting in the CAR region. Histogram equalization of the topographic grids was implemented by partition of the raster grids into equal-area patches of data ranged by the segments with relative highs and lows of the relief. The original data were compared with the equalized, normalized and quadratic models. The scripts used for cartographic data processing are presented and commented. The consistency and equalization of topography, gravity and geoid data were based using GMT modules ‘grdfft’ and ‘grdhisteq’ modules. Using GMT scripts for mapping the geophysical and gravity data over CAR shows an advanced approach to multi-source data visualization to reveal the relationships in the geophysical and topographic processes in central Africa. The results highlighted the correlation between the distribution of rocks with high magnetism in the central part of the Bangui anomaly, and distribution of granites, greenstone belts, and metamorphosed basalts as rock exposure. The correspondence between the negative Bouguer anomaly (<−80 mGal), low geoid values (<−12 m) and the extent of the magnetic anomaly with extreme negative values ranging from −1000 to −200 nT is identified. The integration of the multi-source data provides new insights into the analysis of crustal thicknesses and the average density of the Earth in CAR, as well as the magnitude of the magnetic fields with notable deviations caused by the magnetic flux density in the Bangui area related to the distribution of mineral resources in CAR. Full article

This study analyzes the influences of the mid-level vortex on the formation of Tropical Cyclone Toraji (2013). A rare case of a tropical cyclone that formed near Taiwan involved a mid-level vortex that was a remnant of Tropical Cyclone Kong-Rey (2013). The piecewise potential vorticity inversion method is applied to examine the contribution of the mid-level vortex to the low-level wind field under quasi-balanced conditions. Numerical sensitivity experiments are conducted to quantify the importance of the mid-level vortex on Toraji formation, in which the mid-level vortex is removed with different removing factors (percentages) from the initial field. The results indicate that mid-level positive potential vorticity anomalies significantly contribute to the low-level positive vorticity before Toraji formation. Furthermore, when the removing factors increase in the sensitivity experiments, either the intensity of the simulated low-level vortex or the development trend of pre-Toraji decreases. However, there is no significant relationship between the convection’s magnitude and the intensity of the mid-level vortex. The main difference comes from the mid-level vortex’s intensity, which would result in a greater high-level warm core structure and cause stronger vertical mass flux. In summary, the mid-level vortex plays a critical role in the formation of Toraji. It provides a favorable environment for forming the pre-Toraji vortex by maintaining a high-level warm-core structure, leading to the formation of Toraji. Full article

Current-day volcanic activity in the Azores archipelago is characterized by seismic events and secondary manifestations of volcanism. Remote sensing techniques have been widely employed to monitor deformation in volcanic systems, map lava flows, or detect high-temperature gas emissions. However, using satellite imagery, it is still challenging to identify low-magnitude thermal changes in a volcanic system. In 2010, after drilling a well for geothermal exploration on the northern flank of Fogo Volcano on São Miguel Island, a new degassing and thermal area emerged with maximum temperatures of 100 °C. In the present paper, using the ASTER sensor, we observed changes in the near-infrared signals (15 m spatial resolution) six months after the anomaly emerged. In contrast, the thermal signal (90 m spatial resolution) only changed its threshold value one and a half years after the anomaly was recognized. The results show that wavelength and spatial resolution can influence the response time in detecting changes in a system. This paper reiterates the importance of using thermal imaging and high spatial resolution images to monitor and map thermal anomalies in hydrothermal systems such as those found in the Azores. Full article

The temperature dependence of thermal conductivity and specific heat for detonated nanodiamond ceramics is investigated on specially designed experimental setups, implementing the uniaxial stationary heat flow method and the thermal relaxation method, respectively. Additionally, complementary studies with a commercial setup (Physical Property Measurement System from Quantum Design operating either in Thermal Transport or Heat Capacity Option) were performed. Two types of samples are under consideration. Both ceramics were sintered at high pressures (6–7 GPa) for 11–25 s but at different sintering temperatures, namely 1000 °C and 1600 °C. The effect of changing the sintering conditions on thermal transport is examined. In thermal conductivity κ(T), it provides an improvement up to a factor of 3 of heat flow at room temperature. The temperature dependence of κ(T) exhibits a typical polycrystalline character due to hindered thermal transport stemming from the microstructure of ceramic material but with values around 1–2 W/mK. At the lowest temperatures, the thermal conductivity is very low and increases only slightly faster than linear with temperature, proving the significant contribution of the scattering due to multiple grain boundaries. The specific heat data did not show a substantial difference between detonated nanodiamond ceramics obtained at different temperatures unlike for κ(T) results. For both samples, an unexpected upturn at the lowest temperatures is observed—most likely reminiscent of a low-T Schottky anomaly. A linear contribution to the specific heat is also present, with a value one order of magnitude higher than in canonical glasses. The determined Debye temperature is 482 (±6) K. The results are supported by phonon mean free path calculations. Full article

Due to high computational costs, exploring motif statistics (such as motif frequencies) of a large graph can be challenging. This is useful for understanding complex networks such as social and biological networks. To address this challenge, many methods explore approximate algorithms using edge/path sampling techniques. However, state-of-the-art methods usually over-sample frequent motifs and under-sample rare motifs, and thus they fail in many real applications such as anomaly detection (i.e., finding rare patterns). Furthermore, it is not feasible to apply existing weighted sampling methods such as stratified sampling to solve this problem, because it is difficult to sample subgraphs from a large graph in a direct manner. In this paper, we observe that rare motifs of most real-world networks have “more edges” than frequent motifs, and motifs with more edges are sampled by random edge sampling with higher probabilities. Based on these two observations, we propose a novel motif sampling method, Mosar, to estimate motif frequencies. In particular, our Mosar method samples frequent and rare motifs with different probabilities, and tends to sample motifs with low frequencies. As a result, the new method greatly reduces the estimation errors of these rare motifs. Finally, we conducted extensive experiments on a variety of real-world datasets with different sizes, and our experimental results show that the Mosar method is two orders of magnitude more accurate than state-of-the-art methods. Full article

The Cauca River rises in the Colombian Andes and is the main tributary of the Magdalena River, which drains to the Caribbean Sea. The La Balsa station monitors the Upper Cauca basin and is located just downstream of La Salvajina hydroelectric facility. At this station, the discharge time series for November–January during 1950–2019 shows a statistically significant downward break, and change of distribution after 1986 has been documented after La Salvajina started operation. We assessed the spatio-temporal variability of hydroclimatology in the upper Cauca River basin during the pre- and post-Salvajina dam periods to better understand this break. Post-Salvajina, low (high) discharge events are linked to negative (positive) precipitation and soil moisture anomalies that are greater in magnitude and extension than those recorded in the pre-Salvajina period in response to the more intense El Niño events (more intense and frequent central La Niña events) after 1986. Therefore, it is necessary to consider possible future rainfall scenarios and non-infrastructure measures (i.e., reforestation, territorial planning, integrated watershed management, etc.) to mitigate floods and droughts impacts. The contribution of this study is to provide evidence for the need for foresight in the design of any structural or non-structural flood measures. Full article

The uptake of Ni and other elements by Callitris glaucophylla (white cypress pine), from weathered ultramafic rocks under varying depths of transported regolith cover, is examined at two sites in the Miandetta area, New South Wales, Australia. Results show that C. glaucophylla can accumulate elevated Ni concentrations in the needles (leaves or phyllodes) from underlying Ni-enriched regolith up to two orders of magnitude above the normal micronutrient levels required for the species. Such uptake levels occur in areas with high total Ni in the soil and regolith despite the relatively low mobility of the Ni due to its presence in a low availability form. This highlights the importance of biotic processes in extracting Ni from soil. The needles of C. glaucophylla could provide an effective and convenient sampling medium for reconnaissance biogeochemical exploration for Ni mineralisation and anomalies where transported regolith is less than ~3 m thick. The study has also demonstrated the potential for in situ analysis of Ni and other elements in the needles by portable XRF. Full article