岩石碎片化指数反映了岩石质量的质量,基于TBM道挖掘的实时数据
Xu Li1, Lei-Jie Wu1, Yu-Jie Wang2,3
1Key Laboratory of Urban Underground Engineering of the Ministry of Education, Beijing Jiaotong University, Beijing, 100044, China.
Scientific reports
|June 27, 2023
概括
开发了一个新的岩石碎片化指数 (RFI) 系统,在道钻井机 (TBM) 施工期间实时评估岩石状况 (RC). 该系统使用TBM碎片化数据来克服感知挑战并提高TBM性能.
科学领域:
- 地质技术工程 地质技术工程
- 道技术 道技术
- 岩石机械学 岩石机械学
背景情况:
- 在道钻机 (TBM) 施工期间评估岩石状况 (RC) 由于空间和时间的限制,很难.
- 在TBM操作中实时RC感知现有的方法是有限的.
研究的目的:
- 开发一种新的岩石碎片化指数 (RFI) 系统,用于在TBM施工中实时感知岩石状况.
- 利用TBM碎片化数据创建一个有效的RFI.
主要方法:
- 对现有的岩石碎片化模型进行了全面的审查,以确定候选RFI.
- 分析了来自20198米道的12237个TBM碎片化数据样本.
- 调查了候选RFIs,并根据TBM数据推了一个最佳的RFI系统.
主要成果:
- 识别并验证了新的RFIs,能够反映岩石状况.
- 证明了拟议的RFI可以从实时TBM碎片化数据中提取出来.
- 建立了新的RFIs和实际岩石状况之间的显著相关性.
结论:
- 新的RFI系统有效地解决了在TBM操作中实时感知岩石状况的挑战.
- 拟议的RFIs能够实时分类岩石并预测周围岩石的崩潜力.
- 通过改进的控制和支持措施,RFI系统有可能提高TBM施工性能.
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