基于UNet检测的核电冷源取水隧洞清扫机器人设计OA

To address safety hazards in nuclear power plant cooling water intake tunnels—including silt deposition,marine organism blockages,and crack damage—along with the low efficiency and high risk of traditional manual cleaning,a tunnel cleaning robot is designed integrating a tracked mobile platform with an extendable robotic arm.Three-dimensional modeling of the robot is completed using SolidWorks.Lightweight,corrosion-resistant materials like modified resin are employed,with weight reduction and heat dissipation achieved through hollowed-out structural optimization.An adjustable water spray device and a three-finger gripping mechanism are configured to enhance the removal capability of complex deposits.The control system utilizes a Raspberry Pi 4B as the main controller,integrating BlueOS and Arduino to build a collaborative architecture.Stable long-distance communication is enabled via a power line carrier module.A crack detection model is developed using the UNet neural network.After 80 training iterations,the model achieved an 80%recognition accuracy in field tests.Experimental validation confirmed the robot's structural strength meets tunnel operational requirements and its control response remains stable.A feasible technical solution for automated and safe tunnel cleaning in nuclear power plants is provided.