Coal-Rock Recognition of Intelligent Mining Face Based on the Fusion of Image and Laser Point Cloud

被引：0
|
作者：
Si L. [1 ]
Wang Z. [1 ]
Li J. [1 ]
Wei D. [1 ]
Liang B. [1 ,2 ]
Xiao J. [3 ]
机构：
[1] School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou
[2] Xuhai College, China University of Mining and Technology, Xuzhou
[3] Inner Mongolia Zhahanur Coal Industry Co.，Ltd, Tongliao
来源：
Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis | 2023年 / 43卷 / 02期
关键词：
coal-rock recognition; image point cloud; laser point cloud; point cloud registration; point cloud segmentation;
D O I：
10.16450/j.cnki.issn.1004-6801.2023.02.007
中图分类号：
学科分类号：
摘要：
In order to improve the intelligent level of coal mining face，this paper proposes a novel coal-rock recognition method based on the fusion of image and laser point cloud. Firstly，the three-dimensional reconstruction is used to realize the construction of coal-rock image point cloud containing color information and cutting texture features. Secondly，a coal-rock point cloud registration algorithm based on improved iterative closest point （ICP）algorithm is proposed to improve the search speed and accuracy between point pairs. Then，a coal-rock recognition method based on improved regional growth algorithm is designed. The effectiveness of the improved measures is verified by simulation analysis. The self-established coal-rock cutting experimental system is set up，and the experimental comparison and analysis of the improved ICP and region growth algorithm are carried out. The results indicate that the point cloud data segmentation effect of the proposed method is the best and the accuracy of coal-rock recognition can reach to 92.95%. The field test is carried out in the underground coal face，which further proves the practicability and feasibility of proposed coal-rock recognition method. © 2023 Nanjing University of Aeronautics an Astronautics. All rights reserved.
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页码：254 / 262and407
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