Lightning-induced breaking accidents of medium-voltage insulated conductors pose a serious threat to the safety of distribution networks, and the key cause lies in the establishment and sustained combustion of the power-frequency follow-current arc after lightning overvoltage breakdown. This paper systematically investigates the formation mechanism and critical conditions of power-frequency follow-current arcs using combined simulation and experimental approaches. Based on the streamer discharge theory, a lightning breakdown model was established and combined with the arc energy balance equation, revealing that the establishment of power-frequency follow-current arcs is essentially determined by the post-breakdown energy competition process. The simulation results show that the required anode electric field strength for lightning breakdown is not less than 3 kV/mm. When the power-frequency voltage reaches 10 kV, Joule heating of the arc continuously exceeds heat dissipation loss, enabling restrike after zero-crossing and sustaining stable burning. Experiments verified this voltage threshold and further revealed that the arc establishment rate exhibits nonlinear growth with increasing power-frequency voltage, exceeding 90% at power-frequency voltages ≥ 10 kV. The study also reveals that increased gap distance reduces the arc establishment rate, while the introduction of insulators can enhance it by approximately 20%. This study clarifies the energy criterion for power-frequency follow-current arc establishment and the influence patterns of key parameters, providing theoretical basis and engineering reference for lightning protection design and arc suppression in medium-voltage insulated lines.

Avalanches pose serious threats to critical infrastructure in alpine-cold regions. Synthetic aperture radar (SAR) provides all-day, all-weather observations for avalanche mapping under persistent cloud cover. However, existing SAR change detection methods report accuracies from 0.49 to 0.87 and remain less effective for small avalanches. Their strong dependence on region-specific parameters also limits rapid and transferable avalanche mapping. To address these limitations, this study proposes a Siamese multiscale feature fusion network (SiamNet) for avalanche change detection from Sentinel-1A SAR images. SiamNet employs a shared-weight Siamese encoder to extract multiscale features from the pre- and post-event images and enhance avalanche-related feature responses. Experiments were conducted in the perennial snow-covered area of the typical alpine-cold area in the south-east Tibetan Plateau. A total of 33 avalanches were identified, with an overall accuracy of 98.76%. Field validation showed high agreement between the mapped areas and the actual avalanche tracks and deposits. Compared with representative change detection methods, including FC-Siam-Diff, SNUNet-CD, BIT, ChangeFormer, HANet, and EfficientCD, SiamNet effectively suppresses false detections while reducing missed detections and maintains superior performance across different scenarios. The results demonstrate that SiamNet can effectively map small avalanches with irregular boundaries and complex internal structures, providing technical support for rapid large-area avalanche surveys, spatial mapping, and risk assessment.