李徐然;施富强;廖学燕;李锋;
LI Xu-ran;SHI Fu-qiang;LIAO Xue-yan;LI Feng;School of Mechanical Engineering,Southwest Jiaotong University;Sichuan Academy of Safety Science and Technology;

• 1:西南交通大学机械工程学院
• 2:四川省安全科学技术研究院

摘要(Abstract)：

为了满足光面爆破质量检测技术快速、准确和稳定的要求,结合一爆破现场获取数据,探索光面爆破半孔位置新的识别方法。设计一种使用三维激光点云对光面爆破面进行数据获取,并提取爆破面半孔特征的算法模型。通过将点云数据的颜色特征、反射率特征和曲率特征进行比较,选取了效果较好的半孔特征点进行半孔位置拟合。完成位置拟合后提取半孔点云,并根据半孔点云数据分析半孔的特征。结果表明,该计算模型可以准确、高效的识别半孔特征,并使半孔的识别和分析受光照等外界影响更小,且更为客观准确。与传统方法相比其更好的达到爆破质量检测效果。
In order to satisfy the requirement of fast,accurate and stable detection technology of smooth blasting quality,a new identification method of semi-holes in smooth blasting was explored based on field data.An algorithm model was designed to acquire the data of smooth blasting surface and extract the features of semi-holes from the data of 3 Dlaser point cloud.By comparing the color feature,reflectivity feature and curvature feature of point cloud data,the feature points with better effect were selected to fit the semi-holes position.After completing the position fitting,the semi-holes were extracted,and the characteristic parameters of the semi-holes were analyzed according to the semi-holes data.The results show that the model can identify the features of residual holes accurately and efficiently,and make the recognition and analysis of residual holes less affected by illumination,and more objective and accurate.Comparing with the traditional method,it achieves better blasting quality detection effect.

关键词(KeyWords)： 三维点云;爆破质量;检测技术;光面爆破;半孔率
3D point clouds;blasting quality;detection technology;smooth blasting;semi-holes ratio

Abstract:

Keywords:

基金项目(Foundation):

作者(Authors): 李徐然;施富强;廖学燕;李锋;
LI Xu-ran;SHI Fu-qiang;LIAO Xue-yan;LI Feng;School of Mechanical Engineering,Southwest Jiaotong University;Sichuan Academy of Safety Science and Technology;

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