Search

Rain is one of the dominant meteorological factors threatening the outdoor insulation performance of ultra-high voltage (UHV) power stations. Discharge occurring on the polluted surface of post insulators in rain has always been a major concern of power stations. Previous studies have shown that suspended water droplets on the shed edge play an important role in the rain flashover process. In this work, artificial contamination rain flashover tests were carried out in a laboratory on a UHV DC (Ultra-High Voltage Direct Current) large-diameter composite post insulator, which had a rod diameter of 625 mm and alternating sheds (105 mm and 75 mm for larger and smaller shed overhang, respectively). The discharge mechanism was analyzed base on the observation of discharge phenomenon of suspended water-drops on the shed edge. Moreover, simulation models by COMSOL Multiphysics were established to investigate the electric field around sheds and suspended water-drops, as well as the shape change of water droplets on the insulation surface, especially at the edge of the shed. Results show that the shape parameters of water-droplets changed continuously under the combined action of gravity, surface tension, and capillary tension. Suspended water-droplets on the shed edge showed a great influence on the electric field distribution, and the resulting discharge lead to the bridging between sheds. This work paves a new way to revealing the contamination rain flashover mechanism on post insulators and provides critical knowledge for power stations on preventing flashover accidents.

The discharges of water columns and droplets between the sheds make the leakage distance not effectively used, which is one of the main reasons for flashover of composite post insulators under heavy rainfall. To study the influence of shed parameters on surface rainwater characteristics, artificial rain tests were carried out on the large-diameter composite post insulators under the rainfall intensity of 2–15 mm/min. Lwc (the length of water columns at the edge of large sheds), Nwc (the number of water columns at the edge of large sheds), Nwde (the number of water droplets at the edge of large sheds) and Nwds (the number of water droplets in the space between two adjacent large sheds) were proposed as the parameters of surface rainwater characteristics. The influences of large shed spacing, large shed overhang and rod diameter on the parameters of surface rainwater characteristics under different rainfall intensities were analyzed. The experimental results show that, under the same rainfall intensity, with the rise in large shed spacing, large shed overhang or rod diameter, Lwc, Nwc, Nwde and Nwds all increase. Under different rainfall intensities, the trends of the parameters with the change in shed parameters are basically invariant; however, the change ranges of the parameters are different. The increases in the parameters with the rises in shed parameters and rainfall intensity are mainly attributed to the change in the rainfall on the insulator surface. The experimental results can provide references for the quantitative description of surface rainwater characteristics and the design of large-diameter composite post insulators for DC transmission systems.

The intelligent inspection of power lines and other difficult-to-access structures and facilities has been greatly enhanced by the use of Unmanned Aerial Vehicles (UAVs), which allow inspection in a safe, efficient, and high-quality fashion. This paper analyzes the characteristics of a scene containing power equipment and the operation mode of UAVs. A low-cost virtual scene is created, and a training sample for the power-line components is generated quickly. Taking a vibration-damper as the main object, an assembled detector based on geometrical constraint (ADGC) is proposed and is used to analyze the virtual dataset. The geometric positional relationship is used as the constraint, and the Faster Region with Convolutional Neural Network (R-CNN), Deformable Part Model (DPM), and Haar cascade classifiers are combined, which allows the features of different classifiers, such as contour, shape, and texture to be fully used. By combining the characteristics of virtual data and real data using UAV images, the power components are detected by the ADGC. The result produced by the detector with relatively good performance can help expand the training set and achieve a better detection model. Moreover, this method can be smoothly transferred to other power-line facilities and other power-line scenarios.

The hydrophobicity of composite insulators is a great significance to the safe and stable operation of transmission lines. In this paper, a recognition method of the hydrophobicity class (HC) of composite insulators based on features optimization was proposed. Through the spray method, many hydrophobic images of water droplets on the insulator surface at various hydrophobicity classes (HCs) were taken. After processing of the hydrophobic images, seven features were extracted: the number n, mean eccentricity Eav and coverage rate k1 of the water droplets, and the coverage rate k2, perimeter Lmax, shape factor fc, and eccentricity Emax of the maximum water droplet. Then, the maximum value Δxmax, the minimum value Δxmin, and the average value Δxav of the change rate of each feature value between adjacent HCs, and the volatility Δs of each feature value, were used as the evaluation indexes for features optimization. After this features optimization, the five features that are most closely related to the HC were obtained. Lastly, a recognition model of the HC with the five features as input and the seven HCs as output was established. When compared with the spray method and the contact angle method, the correct rate of the proposed recognition method was 98.1% and 95.2%, respectively. The influence of subjective factors on the spray method was effectively overcome.