Recently, the Xiangyang Emergency Management Bureau and State Grid Xiangyang Power Supply Company conducted special supervision and inspection for Qingming wildfire prevention on site. Through a dual-pronged approach of "manpower + technology" and government-enterprise collaboration, they have woven a dense wildfire prevention and control network to fully ensure the safe and stable operation of power grid equipment, achieving coordinated safety for forests and power infrastructure.
To address the challenges of complex mountainous terrain, low efficiency of manual inspections, and numerous blind spots in Xiangyang, State Grid Xiangyang Power Supply Company has dispatched 48 drones equipped with high-definition cameras and infrared thermal imaging devices. These drones form five professional inspection teams that optimize flight routes for different terrains such as mountains and hills, achieving "full coverage, no blind spots" inspections for transmission lines of 35 kV and above. In particular, the drone-in-a-box systems deployed in key forest areas are equipped with automated docking stations, offering a single flight endurance of up to 40 minutes and a maximum inspection coverage radius of 6 kilometers. After completing a mission, they can automatically return to the station and recharge. They can perform up to 15 inspection flights per day, enabling 24-hour uninterrupted monitoring. Relying on the intelligent drone inspection system and high-definition cameras and infrared detectors installed on towers in 120 key forest areas, Xiangyang has built an integrated "air-ground" monitoring and early warning platform. AI algorithms can identify fire spots and smoke anomalies in seconds, with warning information pushed to staff immediately. Combined with a rapid response mechanism of "drone warning + ground response", fires can be extinguished at an early stage.
To date, more than 1,200 drone inspection flights have been conducted, successfully responding to eight early-stage wildfires, with no incidents of wildfires affecting power grid operations. (By Du Yuan, Li Junlei, Wang Shiqi)
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