Search Results (16)

To satisfy the obstacle avoidance requirements of unmanned agricultural machinery during autonomous operation and address the challenge of rapid obstacle detection in complex field environments, an improved field obstacle detection model based on YOLOv8 was proposed. This model enabled the fast detection and recognition of obstacles such as people, tractors, and electric power pylons in the field. This detection model was built upon the YOLOv8 architecture with three main improvements. First, to adapt to different tasks and complex environments in the field, improve the sensitivity of the detector to various target sizes and positions, and enhance detection accuracy, the CBAM (Convolutional Block Attention Module) was integrated into the backbone layer of the benchmark model. Secondly, a BiFPN (Bi-directional Feature Pyramid Network) architecture took the place of the original PANet to enhance the fusion of features across multiple scales, thereby increasing the model’s capacity to distinguish between the background and obstacles. Third, WIoU v3 (Wise Intersection over Union v3) optimized the target boundary loss function, assigning greater focus to medium-quality anchor boxes and enhancing the detector’s overall performance. A dataset comprising 5963 images of people, electric power pylons, telegraph poles, tractors, and harvesters in a farmland environment was constructed. The training set comprised 4771 images, while the validation and test sets each consisted of 596 images. The results from the experiments indicated that the enhanced model attained precision, recall, and average precision scores of 85.5%, 75.1%, and 82.5%, respectively, on the custom dataset. This reflected increases of 1.3, 1.2, and 1.9 percentage points when compared to the baseline YOLOv8 model. Furthermore, the model reached 52 detection frames per second, thereby significantly enhancing the detection performance for common obstacles in the field. The model enhanced by the previously mentioned techniques guarantees a high level of detection accuracy while meeting the criteria for real-time obstacle identification in unmanned agricultural equipment during fieldwork. Full article

Electrical faults caused by power escaping electric systems can lead to power outages, equipment damage, and fires. Faults sometimes occur when birds perched on power structures are electrocuted. Distribution power lines supported by concrete and steel pylons are particularly fault-prone because small separations between conductors and grounded components allow even small birds to inadvertently create faults while being electrocuted. Most conservation solutions focus on covering energized wires and components to prevent contact by birds and, although usually effective when installed correctly, covers can sometimes be dislodged thus becoming ineffective. Glass Flake Epoxy (GFE) is a non-conductive thermoset plastic that can adhere to steel crossarms and not be dislodged. We hypothesized that GFE-coated crossarms might reduce faults (proxies for avian electrocutions), and we conducted laboratory and field trials to evaluate that hypothesis. In the laboratory, we found a 2000 micrometer (μm)-thick layer of GFE coating that created a dielectric strength of 12.30 ± 0.21 kV, which was sufficient to prevent the formation of a phase-to-ground fault on up to 20 kV distribution lines. This should allow birds to perch on metal crossarms without being electrocuted. In field trials, we substituted 24% of a 20 kV distribution pylon’s crossarms with GFE-treated crossarms and found that doing so correlated with a 28% decrease in faults. Although we did not measure avian electrocutions directly, our findings suggest GFE coatings may offer a novel method of reducing avian electrocutions on power lines. Full article

Electric pylons are crucial components of power infrastructure, requiring accurate detection and identification for effective monitoring of transmission lines. This paper proposes an innovative model, the EP-YOLOv8 network, which incorporates new modules: the DSLSK-SPPF and EMS-Head. The DSLSK-SPPF module is designed to capture the surrounding features of electric pylons more effectively, enhancing the model’s adaptability to the complex shapes of these structures. The EMS-Head module enhances the model’s ability to capture fine details of electric pylons while maintaining a lightweight design. The EP-YOLOv8 network optimizes traditional YOLOv8n parameters, demonstrating a significant improvement in electric pylon detection accuracy with an average mAP@0.5 value of 95.5%. The effective detection of electric pylons by the EP-YOLOv8 demonstrates its ability to overcome the inefficiencies inherent in existing optical satellite image-based models, particularly those related to the unique characteristics of electric pylons. This improvement will significantly aid in monitoring the operational status and layout of power infrastructure, providing crucial insights for infrastructure management and maintenance. Full article

This paper aims to improve the deicing performance and energy utilization of bridge pylon crossbeams with built-in carbon fiber electric heating (BPB–CFEH). Therefore, a three-dimensional thermal transfer model of BPB–CFEH with one arrangement is established. Two ice-melting regions and two ice-melting stages were set up according to the characteristics of the icing of the crossbeam. The effects of wind speed and ambient temperature on the paving power required to reach the complete melting of the icicles within 8 h were analyzed. The effects of the laying spacing and rated voltage of the carbon fiber heating cable on the melting ice sheet and the thermal exchange of the two regions of the icicle after heating for 8 h were compared. Additionally, its effect on energy utilization of the process from the ice sheet melting stage to the ice column melting stage was analyzed. Ice-melting experiments verified the applicability and reasonableness of the simulated ice-melting calculation formula. The results show that under ambient temperature of −10 °C and wind speed of 4.5–13.5 m/s, the proposed paving power is 817.5–2248.12 W/m². Increasing the rated voltage and shortening the spacing increases the thermal exchange capacity of the two melting regions. The shortening of the spacing improves the energy utilization rate of the melting stage of the ice sheet to the melting stage of the icicle processes. The difference between the melting time obtained from the formula proposed by numerical simulation and the melting time obtained from indoor tests is about 10 min. This study provides a design basis for the electrothermal ice melting of bridge pylon crossbeams. Full article

Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (r_crit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from r_crit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards. Full article

Aircraft configurations with propellers have been drawing more attention in recent times, partly due to new propulsion concepts based on hydrogen fuel cells and electric motors. These configurations are prone to whirl flutter, which is an aeroelastic instability affecting airframes with elastically supported propellers. It commonly needs to be mitigated already during the design phase of such configurations, requiring, among other things, unsteady aerodynamic transfer functions for the propeller. However, no comprehensive assessment of unsteady propeller aerodynamics for aeroelastic analysis is available in the literature. This paper provides a detailed comparison of nine different low- to mid-fidelity aerodynamic methods, demonstrating their impact on linear, unsteady aerodynamics, as well as whirl flutter stability prediction. Quasi-steady and unsteady methods for blade lift with or without coupling to blade element momentum theory are evaluated and compared to mid-fidelity potential flow solvers (UPM and DUST) and classical, derivative-based methods. Time-domain identification of frequency-domain transfer functions for the unsteady propeller hub loads is used to compare the different methods. Predictions of the minimum required pylon stiffness for stability show good agreement among the mid-fidelity methods. The differences in the stability predictions for the low-fidelity methods are higher. Most methods studied yield a more unstable system than classical, derivative-based whirl flutter analysis, indicating that the use of more sophisticated aerodynamic modeling techniques might be required for accurate whirl flutter prediction. Full article

Urbanization is a major land use change across the globe with vast effects on wildlife. In this paper, we studied (1) the territorial displays of Little Owls in urban and rural landscapes, analyzing also (2) the size and habitat composition of the territories, and (3) the factors affecting territory size in both landscapes. To do that, we used t-tests, Principal Components Analysis, and General Linear mixed model procedures. The territory size was smaller in urban than in rural landscapes. Urban territories of Little Owls are characterized by a lower cover of grassland, tall crops, short crops, gardens, and orchards, as well as a higher cover of built-up areas than territories in rural landscapes. Territory size in rural landscapes was negatively correlated with seasonal progress and positively correlated with altitude. The rate of territorial displays was similar between urban and rural territories; however, birds differentially utilized various structures. In urban territories, birds mostly used buildings, whereas in rural territories, birds used electric pylons and trees. The compositional differences between territories in the two landscapes may have important consequences for other behavior types and possibly reproductive output in this species. Full article

The aerodynamic design of a new aircraft concept was investigated through subsonic wind-tunnel testing using 1:28-scale powered models. The aircraft configuration integrates a box-wing layout with engines located at the rear part of the fuselage. Measurements involved a back-to-back comparison between two aircraft models: a podded version whose engines were assembled on pylons and a boundary-layer ingestion (BLI) version that provided several system-level benefits. The flowfield was investigated through the power balance method and a variety of pressure flowfield and inlet flow distortion metrics. The results proved that the BLI configuration enhances the propulsive efficiency by reducing both the electrical power coefficient and the kinetic energy waste due to lower jet velocities. Furthermore, there was a reduction of the total pressure recovery due to pressure gradients inside the duct, thereby causing high distortion. Overall, this research highlights the importance of wind-tunnel testing to bring any aerodynamic technology to a sufficient level of maturity and to enable future new aircraft concepts. Full article

The icing of bridge pylon crossbeams is a problem that could pose a serious threat to traffic during a cold winter. However, little research has been carried out on the problem and few corresponding countermeasures have been provided. This paper aims to propose a novel heating system, and to study the feasibility of beam de-icing and the related de-icing strategies so as to provide a reference scheme for the practical application of beam de-icing. A number of icing and de-icing tests were carried out on a scale model of Wuhan Yangtze River Second Bridge in the cold chamber. The de-icing effects of the beam in different environments and different de-icing methods were compared, and the recommended pre-heating time, applicable environment range, and heating method were given. The results of the model experiments show that pre-heating the heating system can prevent the surface of the beam from freezing and that the anti-icing method is more suitable for beam de-icing than the passive de-icing method. When the pre-heating time exceeds 7 min, the entire anti-icing process can be ice-free. When the wind velocity exceeds 5 m/s, it is safer to shut down the heating system, and using the passive de-icing method at the end of the icing can also eliminate the hidden danger of beam icing. Full article

Energy infrastructure is expanding at a global scale and can represent a major threat to wildlife populations. Power lines are one of the main sources of human-induced avian mortality due to electrocution or collision, but many species use electricity pylons as a structure for nesting. Pylon nesting results in human-wildlife conflict because it can cause power outages and structural damage to power lines. The white stork (Ciconia ciconia) is a large-size semicolonial species that increasingly nests on pylons, causing growing operational and economic issues to power companies and energy consumers. In this study, the likelihood of problematic pylon use by nesting storks was predicted using a suite of explanatory variables related to the availability of foraging habitat and human disturbance. During a five-year period (2015–2019), we assessed the distribution of stork nests removed from the highly-risky top part of transmission pylons (220–400 kV) by power company technicians in South western Spain. A total of 839 nests were removed from 11% of the transmission pylons (n = 1196) during the study period. Pylon use intensified on pylons located near to landfills, surrounded by high proportion of grassland, and when close to freshwater sources (water body or river) and other occupied pylons. Human disturbance was unlikely to deter storks from using pylons and pylon use increased in urban areas. The approach used here to predict pylon use by nesting birds has applications for both human-wildlife conflict mitigation and conservation purposes where endangered species use human infrastructure. Power companies may use this kind of information to install anti-nesting devices (to reduce power outages and avian mortality or nesting platforms on suitable pylons (to promote pylons use by endangered species), and to account for the likelihood of conflict-prone use of pylons when siting future power lines. Full article

High-voltage and ultra-high-voltage overhead power lines are important to meet the electricity demand of our daily activities and productions. Due to the overgrowth of trees/vegetation within the corridor area, the distance between the power lines and its surroundings may break through the safety threshold, which could cause potential hazards such as discharge and fire. To ensure the safe and stable operation of the power lines, it is necessary to survey them regularly so that the potential hazards from the surroundings within the power line corridor could be investigated timely. This paper is motivated to quickly and accurately survey the power line corridor with the 3D point clouds. The main contributions of this paper include: (1) the spatial line clustering is proposed to accurately classify and complete the power line points, which can greatly overcome the sparsity and missing of LiDAR points within the complex power line corridor. (2) The contextual relationship between power lines and pylon is well investigated by the grid-based analysis, so that the suspension points of power lines on the pylon are well located. (3) The catenary plane-based simplification of 3D spatial distance calculation between power lines and ground objects facilitates the survey of the power line corridor. Experimental results show that the accuracy of safety distance surveying is 5 cm for power line corridors of all voltage levels. Compared to the ground-truth point-to-point calculation, the speed of surveying is enhanced thousands of times. It is promising to greatly improve both the accuracy and efficiency of surveying the potential hazards of power line corridor. Full article

Although climate change is well recognised as an important issue in Japan, there has been little interest from scientists or the public on the potential threat it poses to heritage. The present study maps the impact of emerging pressures on museums and historic buildings in the Tokyo Area. We examine a context to the threat in terms of fluctuating levels of visitors as a response to environmental issues, from SARS and COVID-19, through to earthquakes. GIS mapping allows a range of natural and human-induced hazards to be expressed as the spatial spread of risk. Temperature is increasing and Tokyo has a heat island which makes the city hotter than its surroundings. This adds to the effects of climate change. Temperature increases and a decline in relative humidity alter the potential for mould growth and change insect life cycles. The region is vulnerable to sea level rise, but flooding is also a likely outcome of increasingly intense falls of rain, especially during typhoons. Reclamation has raised the risk of liquefaction during earthquakes that are relatively frequent in Japan. Earthquakes cause structural damage and fires after the rupture of gas pipelines and collapse of electricity pylons. Fires from lightning strikes might also increase in a future Tokyo. These are especially relevant, as many Japanese heritage sites use wood for building materials. In parallel, more natural landscapes of the region are also affected by a changing climate. The shifting seasons already mean the earlier arrival of the cherry blossom and a later arrival of autumn colours and a lack of winter snow. The mapping exercise should highlight the spatial distribution of risk and the way it is likely to change, so it can contribute to longer term heritage management plans. Full article

The working condition of power network can significantly influence urban development. Among all the power facilities, electric pylon has an important effect on the normal operation of electricity supply. Therefore, the work status of electric pylons requires continuous and real-time monitoring. Considering the low efficiency of manual detection, we propose to utilize deep learning methods for electric pylon detection in high-resolution remote sensing images in this paper. To verify the effectiveness of electric pylon detection methods based on deep learning, we tested and compared the comprehensive performance of 10 state-of-the-art deep-learning-based detectors with different characteristics. Extensive experiments were carried out on a self-made dataset containing 1500 images. Moreover, 50 relatively complicated images were selected from the dataset to test and evaluate the adaptability to actual complex situations and resolution variations. Experimental results show the feasibility of applying deep learning methods to electric pylon detection. The comparative analysis can provide reference for the selection of specific deep learning model in actual electric pylon detection task. Full article

(1) Background: The visual impact of artificial infrastructures on natural landscapes generates a common negative perception in public opinion. However, as in the case of electrical energy, the increasing demand for power supply and its need for capillary distribution require the installation of new lines, commonly overhead lines with tall tower-like pylons. In most countries, this situation is faced with many attempts of solutions, as participatory workshops and design contests. Nevertheless, the solutions are usually not further developed into real structures due to many limitations (e.g., regulatory, safety, lack of feasibility). (2) Methods: This paper presents a systematic method for the design of tower-like pylons (e.g., electric ones) able to improve the visual quality on the landscape areas in which they will be installed. The method identifies a design strategy that advantageously exploits the inevitable visual impact of pylons on the landscape by integrating the symbolic morphology and the topologically optimized pylon structure from the earliest design phases. (3) Results: The resulting structure is designed in three steps. First, a concept is morphologically developed by integrating symbolic references to the landscape, environment, or cultural society. Second, the concept is topologically optimized, by reducing the structural weight and its visual impact, and respecting regulatory requirements. Third, the resulting structure is engineered and embodied into an industrially feasible layout. (4) Conclusions: The method is able to develop an original, brand new tower-like pylon integrating all the types of requirements, such as regulatory, industrial feasibility, and social components’ needs. The resulting electricity pylon presents an enhanced visual quality according to the citizens’ feedback. Full article

Electric power transmission and maintenance is essential for the power industry. This paper proposes a method for the efficient extraction and classification of three-dimensional (3D) targets of electric power transmission facilities based on regularized grid characteristics computed from point cloud data acquired by unmanned aerial vehicles (UAVs). First, a spatial hashing matrix was constructed to store the point cloud after noise removal by a statistical method, which calculated the local distribution characteristics of the points within each sparse grid. Secondly, power lines were extracted by neighboring grids’ height similarity estimation and linear feature clustering. Thirdly, by analyzing features of the grid in the horizontal and vertical directions, the transmission towers in candidate tower areas were identified. The pylon center was then determined by a vertical slicing analysis. Finally, optimization was carried out, considering the topological relationship between the line segments and pylons to refine the extraction. Experimental results showed that the proposed method was able to efficiently obtain accurate coordinates of pylon and attachments in the massive point data and to produce a reliable segmentation with an overall precision of 97%. The optimized algorithm was capable of eliminating interference from isolated tall trees and communication signal poles. The 3D geo-information of high-voltage (HV) power lines, pylons, conductors thus extracted, and of further reconstructed 3D models can provide valuable foundations for UAV remote-sensing inspection and corridor safety maintenance. Full article