Prof. Jun Guo Profile

Prof. Jun Guo

at Northeastern Univ

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Proceedings Article | 31 October 2022 Paper

Tunnel punching inclination correction method based on three-laser rangefinder

Aixuan Dong, Jun Guo, Jingwei Song, Kai Li, Zixuan Zhao

Proceedings Volume 12457, 124570W (2022) https://doi.org/10.1117/12.2660969

KEYWORDS: Laser drilling, Error analysis, Stereoscopic cameras, Laser range finders, 3D image processing, Laser damage threshold, Distance measurement

Read Abstract +

At present, tunnel drilling inclination correction mostly uses the traditional method of inclination prediction and correction of tunnel drilling with worker experience and special inclination and measurement equipment. This method has low efficiency, high working intensity and low equipment utilization rate. On this basis, some other methods have been proposed to use 3D image technology to calculate the position inclination of tunnel punching points with industrial-grade 3D cameras. However, the accuracy of the above methods is not high. In order to solve the above two problems and realize the high precision vertical drilling of the computer fully automatic control punching robot, this paper proposes a tunnel drilling inclination correction method based on three-laser rangefinder. First, the computer communicates with the laser rangefinder to obtain the measurement results of three-laser rangefinder; second, calculating the distance between three points to determine whether the section between the drill and the punched point can be offset; finally, calculating the inclination correction and adjusting the execution end attitude. Experiments show that compared with the existing artificial drilling technology or calculating the tunnel hole position inclination with the help of industrial 3D camera using 3D image technology, this method has higher accuracy and drilling efficiency, good breakthrough has been made in reducing cost and improving efficiency. It can also meet the requirements of equipment stability in the harsh tunnel environment.

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