Unmanned aerial vehicle tunnel defect detection method and system

Abstract

The invention relates to an unmanned aerial vehicle tunnel defect detection method and system, an unmanned aerial vehicle carries an LED module, a camera, a laser radar, an ultrasonic range finder and an IMU, and the method comprises the following steps: collecting images in a tunnel based on the LED module and the camera to obtain a training image set; training by using the training image set to obtain a defect detection model; collecting real-time tunnel images, performing suspected defect detection on the real-time tunnel images through the defect detection model, obtaining unmanned aerial vehicle pose information based on the camera, the laser radar, the ultrasonic range finder and the IMU, and controlling the unmanned aerial vehicle to hover. Compared with the prior art, the LED module is used for supplementing illumination in the tunnel, the IMU, the camera, the laser radar and the ultrasonic range finder are fused to achieve unmanned aerial vehicle pose estimation, the trained defect detection model is used for detecting whether suspected defects exist or not in real time, hovering is carried out after the suspected defects are found, and defect detection is further carried out. Accurate pose estimation and defect detection can be realized in a tunnel which has no GPS signal and is highly symmetrical inside.

Description

technical field [0001] The invention relates to the field of unmanned aerial vehicle inspection, in particular to a method and system for detecting defects in an unmanned aerial vehicle tunnel. Background technique [0002] In recent years, my country's infrastructure facilities, such as underground subway tunnels, railway tunnels and high-speed tunnels, have entered an "aging" period after long-term use, requiring regular maintenance and inspection, otherwise it will cause disastrous consequences. However, traditional maintenance requires a lot of manpower and material resources, and there are problems such as heavy workload, high risk factor, and harsh working environment. Therefore, it is urgent to use drones for facility maintenance. UAVs are flexible, agile, and can easily reach places that humans cannot reach. [0003] In the existing technology, the UAV flies autonomously during the inspection process, uses GPS signals for positioning, and updates the location inform...

AI Technical Summary

Problems solved by technology

[0004] However, when performing tunnel defect detection, due to the weak light in the tunnel, and even dark areas, the collected images are often of low quality

Moreover, GPS technology cannot be used in the tunnel, and the positioning error of the UAV continues to accumulate over time. Since the tunnel is a highly symmetrical structure, there are almost no other geometric features and textures, which also gives the UAV position in multiple degrees of freedom. pose estimation poses challenges

Due to insufficient positioning accuracy, after the tunnel defect is found based on the image, the returned position information also has a large error

Therefore, the existing technology cannot meet the requirements of tunnel defect detection

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