摘要
随着我国经济与科学技术的发展以及大规模多数量基建工程建设爆发期的到来,TBM凭借其高效、优质、安全、环保、自动化程度高的特点被越来越广泛地应用。但是由于地下地质情况难以进行精确地描述以及前期地质勘察资料准确性不足,常常导致TBM设备对围岩条件适应性差、施工速度慢,甚至存在被卡被困和被损坏的风险。本文以某TBM工程为背景,将收集到的掘进数据清洗后建立围岩类别变化与掘进参数之间的相关性关系,采用建立掘进特征参数与围岩级别线性回归预测模型的方法,得到可靠的围岩识别结果,研究成果对TBM安全高效施工、降低TBM施工风险具有一定参考价值。
With the development of national economy and science&technology and the advent of the construction surge of large-scale infrastructure projects,TBM has found wider and wider applieations thanks to its high eff-ciency,high quality,safety,environment friendliness,and high degree of automation.However,due to the diff-culty in accurately describing the underground geological conditions and the lack of accuracy of early-stage geo-logical survey data,TBM equipment is often hard to adapt to surrounding rock conditions and slow in construction speed,and even risk being stuck and damaged.This peper,taking a TBM projeet as the background,after cleaning the olleeted excavation data,cstablished the correlation between the types of surrounding rocks and the excavation parameters.The linear regression prediction model so established for the excavation characteristic pa-rameter Field Penetration Index and the surounding rock classification has proved reliable to identify the sur-rounding rocks.The research findings can hep improwe TBM construction efficiency and safety and reduce the TBM construetion risks.
作者
徐飞
王忠顺
杜立杰
全永威
赵向波
单鹏飞
Xu Fei;Wang Zhongshun;Du Lijie;Quan Yongwei;Zhao Xiangbo;Shan Pengfei(Key Laboratory of Railway Industry of Infmastructure Safety and Emergency Response,Shijiazhuang Tiedao University,Shijiazhuang,Hebei 050043,China;School of Civil Engi neeing,Shijiazhuang Tiedao University,Shijiazhuang,Hebei 050043,China;School of Mechanical Engineering,Shijazhuang Tiedao University,Shijiazhuang,Hebei 050043,China;Xinjiang Itysh River Investment and Development(Group)Co,Ltd,Urunqi,Xinjiang 80000,China)
出处
《铁道技术标准(中英文)》
2022年第11期1-6,共6页
Railway Technical Standard(Chinese & English)
基金
新疆某重大工程科技计划项目(EQ075/FY056)
国家自然科学基金(52078311)
河北省青年拔尖人才项目(BJ2020055)
中国博士后科学基金(2019M663553)。
关键词
TBM
掘进参数
特征参数
围岩识别
TBM
tunneling parameters
characteristic parameter
identifcation of surrounding rock