Flashover accidents on high-voltage bushings frequently occur under extreme rainfall, which is generally attributed to the bridging of adjacent sheds by pendant drops, a result of the dynamic deformation of pendant drops. We numerically investigate the effects of the parameters of pendant drops and the electric field on the dynamic deformation of pendant drops on a 500 kV transformer bushing under extreme rainfall and verify the simulation results by artificial rain experiment. The dynamic deformation of pendant drops is described by solving the Navier-Stokes equations and using the level set method. The results show that the maximum length of the pendant drop increases with the increase in the initial diameter and the initial mass flow rate, respectively, but decreases under the electric field. The main influencing factor on the maximum length of the pendant drop alters with the variation of the initial diameter and the initial mass flow rate in the absence of the electric field, whereas the initial mass flow rate is the unique main influencing factor in the presence of the electric field. Furthermore, the variations of the maximum length and breakup time of the pendant drop are elucidated by the instability of the pendant drop.

Abstract:Icing on transmission lines might lead to ice flashovers of insulators, collapse of towers, tripping faults of transmission lines, and other accidents. Shed spacing and shed overhang of insulators are clues for evaluating the probability of ice flashover. This paper researches imageprocessing methods for the natural icing of in-service glass insulators. Calculation methods of graphical shed spacing and graphical shed overhang are proposed via recognizing the convexity defects of the contours of an icing insulator string based on the GrabCut segmentation algorithm. The experiments are carried out with image data from our climatic chamber and the China Southern Power Grid Disaster (Icing) Warning System of Transmission Lines. The results show that the graphical shed overhang of insulators show evident change due to icing. This method can recognize the most serious icing conditions where the insulator sheds are completely bridged. Also, it can detect bridging positions including the left side, right side, or both sides of the insulator strings in the images.

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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.

Insulator icing endangers the safe operation of overhead power lines. The current measures for image monitoring of icing overhead power lines rely on manual observation. There is an urgent need for image intelligent analysis methods with strong generalisation, accuracy, and efficiency to improve power grid decision‐making. Based on the icing monitoring data from China Southern Power Grid, this paper first proposes rules for insulator image data cleaning, classification, and annotation, establishing a dataset of insulator icing monitoring images during 2014–2018. Then, based on Yolo (You only look once) v5, a weakly supervised and phased transfer learning method is proposed to recognise insulators and ice types such as snow, rime, mixed rime, glaze, and the normal. This method reduces the interference of icing background, uneven illumination, and camera occlusion through multidimensional feature fusion. The precision, recall, and mean average precision of the recognition can reach 86.6%, 91.3%, and 90.1%, respectively, and the recognition speed is as fast as 8 ms/image. Using image pseudo‐labelling based on weakly supervised learning enables the intellectualisation of image annotation, which significantly changes the inefficiency of manual labelling.