Research on anomaly identification imaging with continuous advanced detection of excavation

被引：0

作者：

Xu S. ^{[1
]}

Lu W. ^{[1
]}

Wang C. ^{[1
]}

Lin J. ^{[2
]}

Xing F. ^{[3
]}

机构：

[1] School of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou

[2] State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin

[3] Xuzhou College of Industrial Technology, Xuzhou

来源：

Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | 2023年 / 44卷 / 11期

关键词：

abnormal body identification imaging; continuous advanced detection during excavation; electrical advanced detection; imaging accuracy;

D O I：

10.19650/j.cnki.cjsi.J2311450

中图分类号：

O212 [数理统计];

学科分类号：

摘要：

This article proposes a new method for continuous advanced detection and imaging of abnormal body during excavation. The problem of poor accuracy in single imaging with fixed field sources is effectively addressed. It provides strong support for parallel operation of tunnel excavation and forward detection. Firstly, a theoretical model for continuous advanced detection and imaging of abnormal body during excavation is formulated. Then, the imaging effect and accuracy improvement methods for abnormal body identification are studied. On the basis of effectively identifying the geometric shape of the abnormal body ahead, the mean square error of conductivity is reduced from 0.273 to 0.156 by increasing the excavation mileage, from 0.173 to 0.153 by increasing the potential sampling frequency, and from 0.183 to 0.167 by increasing the number of potential measurement points. The imaging accuracy is gradually increased. Finally, the imaging effect of anomalies with different types and shapes in front of the field source during excavation is analyzed. A mud trough experimental system is established, and comparative experiments on imaging effects are carried out. The effectiveness of this method is evaluated. © 2023 Science Press. All rights reserved.

引用

页码：159 / 175

页数：16

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