长江科学院院报 ›› 2023, Vol. 40 ›› Issue (1): 123-131.DOI: 10.11988/ckyyb.20210916

• 岩土工程 • 上一篇    下一篇

基于GRU算法的盾构掘进参数预测——以成都地铁19号线为例

肖浩汉1, 陈祖煜1, 徐国鑫2, 蒋宗全3, 苏岩2, 曹瑞琅1, 刘诗洋4   

  1. 1.中国水利水电科学研究院 岩土工程研究所,北京 100048;
    2.陕西省引汉济渭工程建设有限公司,西安 710010;
    3.中电建铁路建设投资集团有限公司,北京 100038;
    4.同济大学 软件学院,上海 200092
  • 收稿日期:2021-08-30 修回日期:2021-10-26 出版日期:2023-01-01 发布日期:2023-02-24
  • 通讯作者: 陈祖煜(1943-),男,浙江宁波人,中国科学院院士,正高级工程师,博士,主要研究方向为岩土工程。E-mail:chenzy@tsinghua.edu.cn
  • 作者简介:肖浩汉(1993-),男,河北衡水人,工程师,博士,主要研究方向为大数据挖掘和智能化掘进。E-mail:xiaohh@iwhr.com
  • 基金资助:
    引汉济渭建设有限公司科技项目(SPS-D-08);陕西省自然科学基金项目(2019JLP-23,2019JLZ-13,2021JLM-50);陕西省联合基金资助项目(2021JLM-53);中国电力建设股份有限公司核心攻关技术项目(DJ-HXGG-2021-01)

Prediction of Shield Tunneling Parameters Based on GRU Algorithm: A Case Study on Chengdu Metro Line 19

XIAO Hao-han1, CHEN Zu-yu1, XU Guo-xin2, JIANG Zong-quan3, SU Yan2, CAO Rui-lang1, LIU Shi-yang4   

  1. 1. Department of Geotechnical Engineering,China Institute of Water Resources and Hydropower Research, Beijing 100038,China;
    2. Hanjiang-to-Weihe River Valley Water Diversion Project Construction Co.,Ltd., Xi'an 710010,China;
    3. China Power Railway Construction Investment Group Co.,Ltd.,Beijing 100038,China;
    4. School of Software Engineering,Tongji University,Shanghai 200092,China
  • Received:2021-08-30 Revised:2021-10-26 Online:2023-01-01 Published:2023-02-24

摘要: 刀盘扭矩和刀盘推力是保障盾构机正常掘进的关键参数,对其准确预测可有效指导设备运行。本项研究的数据来源于成都地铁19号线土压平衡(EPB)盾构机的掘进数据。深入剖析了EPB盾构掘进数据的特点,提出了一种包含数据分割、异常值处理、数据降噪和数据编译4个阶段的标准数据预处理算法。在Butterworth滤波器基础上,利用门控循环单元(GRU)建立了盾构掘进参数预测模型,基于RMSE和MAE指标综合评估预测模型的预测效果。结果表明:预测模型对不同地质条件下的刀盘扭矩和刀盘推力掘进参数均能实现良好预测;经过Butterworth滤波,预测模型的预测精度提高显著;砂岩地层中,预测模型对刀盘扭矩的预测误差最小,RMSE和MAE分别为4.91和3.86。基于GRU算法的掘进参数预测,可提高盾构机掘进状态的判断水平,利于施工参数优化调整。

关键词: 掘进参数预测, 数据预处理, Butterworth滤波, GRU算法, 土压平衡盾构机

Abstract: Cutterhead torque (T) and cutterhead thrust (F) are key parameters to ensure the normal tunneling of shield machine,and their accurate prediction can effectively guide equipment operation.The research datasets are collected from earth pressure balance (EPB) shield machine on line 19 of the Chengdu Metro.By analyzing the characteristics of EPB data,we develop a standard data preprocessing algorithm that includes data segmentation,outlier processing,data filtering and data compilation.Based on Butterworth filter,we establish the prediction model of EPB tunneling parameters by gated recurrent unit (GRU) algorithm,and then comprehensively assess the prediction effect of the model by RMSE and MAE.Results manifest that the proposed model can achieve good prediction for T and F under different geological conditions,and the prediction accuracy of the GRU model in fusion with Butterworth filter is better than that of the unfiltered model.In sandstone formation,the prediction error of the model for T is the smallest,and the RMSE and MAE are 4.91 and 3.86,respectively.The prediction of tunneling parameters based on GRU algorithm can significantly improve the judgment level of shield tunneling state,which is conducive to the optimization and adjustment of construction parameters.

Key words: tunneling parameters prediction, data preprocessing, Butterworth filter, GRU algorithm, earth pressure balance shield machine

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