To address the needs of deep-buried oil and gas pipeline inspection and supervision, as well as the problems of low efficiency, poor timeliness, and low safety of conventional manual inspections, we design and develop a UAV oil/gas pipeline inspection system which combines UAV, convolutional neural network algorithms, and computer system integration technologies. Firstly, we introduce the overall design plan and operation flow of the patrol inspection system. Secondly, we present the system components. The system consists of four subsystems:UAV flight platform, neural network target detection system, UAV inspection management system, and enforcement terminals. The UAV flight platform uses oil-moving fixed-wing UAVs as the flight carrier, carries high-definition cameras for data acquisition, and the neural network target detection system automatically reads the image data, to detect, identify, and search the hidden dangers of engineering vehicles and pipelines along the route. The UAV inspection management system realizes the storage, management, and distribution of data information. The enforcement terminals receive hidden target information and perform rapid on-site enforcement. Finally, the application of the system and the subsequent development direction are summarized and forecasted. The system has been successfully applied to oil and gas pipeline inspection and supervision operations in Henan, Gansu, and other provinces. The results show that the system meets the field needs of oil and gas pipeline inspection and supervision.