首页|基于3D激光感知的隧道爆破参数优化设计方法

基于3D激光感知的隧道爆破参数优化设计方法

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为解决隧道爆破质量控制困难的问题,探究新型爆破参数优化方法,提出一种 3D激光扫描技术与BP神经网络相结合的实时优化方法,对隧道爆破超欠挖感知及其后续钻爆参数进行实时修正,构建现场扫描方法、数据处理、点云提取与超欠挖图像等工作程序,建立BP神经网络模型、算法并确定模型参数.通过试验验证表明:1)将 3D激光扫描技术应用于隧道爆破超欠挖质量感知中切实可行,与人工测量结果吻合较好,具有快速、实时和准确的优点;2)采用 3D激光扫描方法能够对隧道爆破后的断面轮廓线进行精确评测,在获取爆破超欠挖的精细数据后,通过样本学习完成模型训练能推理出较为合理的爆破参数,改进后的优化方案使平均超挖降低 54.8%.
Tunnel Blasting Parameters Optimization Design Method Based on Three-Dimensional Laser Sensing
During tunnel blasting construction,the blasting quality is difficult to control.Therefore,a real-time blasting parameter optimization method based on three-dimensional(3D)laser scanning technology and back propagation(BP)neural network is proposed.This method percepts the over-and under-excavation of tunnel blasting and corrects subsequent drilling and blasting parameters in real time.The working procedures of field scanning method,data processing,point cloud extraction,and over-and under-excavation images are constructed.Finally,the BP neural network model,algorithm,and model parameters are established.The verification test results show that:(1)It is feasible to apply 3D laser scanning technology to the over-and under-excavation quality perception of tunnel blasting,which is in good agreement with the manual measurement results,and has the advantages of fast,real-time,and accurate.(2)The 3D laser scanning method can accurately evaluate the profile line of the tunnel after blasting.After obtaining precise data on blasting over-and under-excavation,the model training can be completed through sample learning to infer reasonable blasting parameters.The improved optimization scheme reduces the average over excavation by 54.8%.

tunnelthree-dimensional laser scanningback propagation neural networkblasting parameters optimizationover-and under-excavation identification

肖清华、袁浩、夏金选、欧小强、臧熙玮、钟德超、刘志强

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西南交通大学,四川 成都 610031

中铁开发投资集团有限公司,云南 昆明 650500

中铁西南科学研究院有限公司,四川 成都 611731

隧道 3D激光扫描 BP神经网络 爆破参数优化 超欠挖识别

中国中铁股份有限公司科技研究开发计划项目中铁开发投资集团有限公司科技研究开发计划项目

实用技术2022-专项-012022-B类-05

2024

10.3973/j.issn.2096-4498.2024.S1.002

隧道建设(中英文)
中铁隧道集团有限公司洛阳科学技术研究所

隧道建设(中英文)

CSTPCD北大核心
影响因子：0.785
ISSN：2096-4498
年,卷(期)：2024.44(z1)
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