测绘通报 ›› 2021, Vol. 0 ›› Issue (1): 157-160,164.doi: 10.13474/j.cnki.11-2246.2021.0030

• 测绘地理信息技术应用案例 • 上一篇    下一篇

基于机器学习的多施工参数盾构施工姿态预测

夏汉庸1, 尹和军2, 徐教煌2, 王嘉伟2, 黄毅1   

  1. 1. 宁波轨道交通集团有限公司, 浙江 宁波 315000;
    2. 中铁工程设计咨询集团有限公司, 北京 100055
  • 收稿日期:2020-12-01 发布日期:2021-02-08
  • 作者简介:夏汉庸(1983-),男,硕士,高级工程师,研究方向为城市轨道地下隧道工程。E-mail:86104554@qq.com

Multi-construction parameter shield construction attitude prediction based on machine learning

XIA Hanyong1, YIN Hejun2, XU Jiaohuang2, WANG Jiawei2, HUANG Yi1   

  1. 1. Ningbo Rail Transit Group Co., Ltd., Ningbo 315000, China;
    2. China Railway Engineering Consulting Group Co., Ltd., Beijing 100055, China
  • Received:2020-12-01 Published:2021-02-08

摘要: 针对盾构施工过程中参数易变、轴线难以预测控制的问题,本文提出了基于机器学习的多施工参数盾构施工姿态预测方法,分析了在复杂环境下影响盾构姿态掘进施工的参数,以及掘进参数和盾构姿态内在的关联关系,建立了盾构姿态预测模型,实现了盾首盾尾中心坐标与设计轴线的偏差计算;最后结合某地铁施工段,验证了该预测模型的可行性。

关键词: 盾构施工, 掘进参数, 机器学习, 盾构姿态, 预测模型

Abstract: This paper proposes a multi-construction parameter shield construction attitude prediction method based on machine learning, analyzes the construction parameters of shield tunneling in complex environment, analyzes the internal relationship between tunneling parameters and shield attitude, and establishes the predicted shield attitude. The prediction model realizes the deviation calculation between the center coordinates of the shield head and the design axis. Combined with a subway construction section, the prediction model is verified.

Key words: shield construction, tunneling parameters, machine learning, shield attitude, prediction model

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