Inspection Robot and Wall Surface Detection Method for Coal Mine Wind Shaft

Abstract

The coal mine wind shaft is an important ventilation channel in coal mines, and it is of great significance to ensure its long-term safety. At present, the inspection of wind shafts still depends on manual work, which has low reliability and high risk. There are two main problems in the shaft wall detection of ventilation shafts: (1) The humidity and dust concentration in ventilation shafts are high, which makes imaging difficult; (2) the cracks on the shaft wall are long and irregular, so it is impossible to acquire the information of the whole crack from a single photo. Firstly, the mapping analysis between the concentration of water vapor and dust in the wind shaft and the image definition is determined by experiments. Then, the inspection robot is designed to move along the axial and circumferential directions to get close to the shaft wall, and the rack-and-rail drive design is adopted to ensure the real-time position feedback of the robot. Then, through the crack parameter detection method based on depth learning, the movement direction of the robot is controlled according to the crack direction so as to ensure that the complete crack parameters are obtained. Finally, the crack detection algorithm is verified by experiments.

Keywords

• wind shaft
• inspection robot
• machine vision
• defect detection