"The inspection results report form for the 20 college entrance examination power supply lines has been generated, and no new defects were found on the abundance." On June 7, State Grid Shenyang Power Supply Company's power supply company's power supply line inspection work completed the inspection work of the college entrance examination power supply lines in front of the computer. This not only marks the official launch of the "Air Command" built by State Grid Shenyang Power Supply Company based on the drone smart phone nest, but also the first show of this technology at the college entrance examination power supply site.
State Grid Shenyang Power Supply Company employees remotely dispatch drones at the "Air Command" to carry out college entrance examination power line inspection
In order to further explore the scenario integration value of drones in power operation and inspection and expand application boundaries, State Grid Shenyang Power Supply Company piloted the deployment of three drone intelligent aircraft nests in Heping District. By simulating the efficient scheduling logic of the aviation command system, it has created an "air command" for power grid inspection drones that integrates "independent take-off and landing, energy supply, data processing, and task planning" functions, allowing power inspection personnel to completely move from "artificial running errands" to "cloud control" and use scientific and technological means to improve the power supply operation and maintenance level.
At 7 a.m. that day, before the college entrance examination candidates entered the examination room, the operation and inspection personnel far away at the "Air Command" had completed the power supply line inspection of 8 test sites through the system. After the drone returned, the inspection data would be automatically uploaded to the drone control system. Operations and inspection personnel import the inspection data into the AI image defect recognition system, and generate inspection results report through the power distribution defect detection algorithm with multi-scale feature fusion technology, providing reference for lean operation and maintenance of the line.
The traditional autonomous inspection of drones relies on manual control and on-site deployment, and faces pain points such as limited battery life, lagging data back-passing, and insufficient response to complex environments. After the "Air Command" takes office, the drone can accurately return to the air and "return to the nest" after completing the inspection mission, achieving "once charge and fly", and the daily inspection time is increased by more than 3 times; key hidden danger information can be directly reached to the operation and maintenance terminal within 5 minutes, allowing the investigation of hidden dangers to shift from "post-processing" to "pre-warning". In practical applications, the three drone smart machine nests can also form "system operation" capabilities, and the inspection radius of each machine nest is 3 kilometers. On the basis of efficient execution of inspection tasks, it can also be used as backup for each other and quickly respond and support temporary fault search, project acceptance, on-site safety control and other tasks.
In the early stage of his post in the "Air Command", Qu Yuanxu, who has the qualification of a captain of the visual range, led the drone inspection team to debug the drone intelligent aircraft nest and drone control system, and carried out tackling technical difficulties such as drone inspection route formulation and cross-system docking of inspection data, formulated 168 inspection routes suitable for airspace flight in the peaceful area, and compiled the "Photo-Pole" basic data-related data software, which compressed the inspection duration from multiple links such as on-site inspection, data processing, dispatching and command, and improved patrol efficiency.
State Grid Shenyang Power Supply Company employees discuss drone college entrance examination power supply line patrol routes
At the same time, the team also tried to integrate drone inspections on 12 routes with AI big models. When the drone inspects cable routes, real-time video streaming data is used, combined with real-time AI to identify broken engineering vehicles, accurately identify operation dynamics of large-scale engineering vehicles, and send early warning information in real time to curb the occurrence of external damage to power lines from the source. (Correspondent Shi Lingfeng)
