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一种新型电磁地下位移传感器的位移参数反演

Displacement parameter inversion for a novel electromagnetic underground displacement sensor.

作者信息

Shentu Nanying, Li Qing, Li Xiong, Tong Renyuan, Shentu Nankai, Jiang Guoqing, Qiu Guohua

机构信息

College of Mechatronics Engineering, China Jiliang University, Hangzhou 310018, Zhejiang, China.

National Engineering Research Center of Advanced Rolling, University of Science & Technology Beijing, Beijing 100083, China.

出版信息

Sensors (Basel). 2014 May 22;14(5):9074-92. doi: 10.3390/s140509074.

DOI:10.3390/s140509074
PMID:24858960
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4063035/
Abstract

Underground displacement monitoring is an effective method to explore deep into rock and soil masses for execution of subsurface displacement measurements. It is not only an important means of geological hazards prediction and forecasting, but also a forefront, hot and sophisticated subject in current geological disaster monitoring. In previous research, the authors had designed a novel electromagnetic underground horizontal displacement sensor (called the H-type sensor) by combining basic electromagnetic induction principles with modern sensing techniques and established a mutual voltage measurement theoretical model called the Equation-based Equivalent Loop Approach (EELA). Based on that work, this paper presents an underground displacement inversion approach named "EELA forward modeling-approximate inversion method". Combining the EELA forward simulation approach with the approximate optimization inversion theory, it can deduce the underground horizontal displacement through parameter inversion of the H-type sensor. Comprehensive and comparative studies have been conducted between the experimentally measured and theoretically inversed values of horizontal displacement under counterpart conditions. The results show when the measured horizontal displacements are in the 0-100 mm range, the horizontal displacement inversion discrepancy is generally tested to be less than 3 mm under varied tilt angles and initial axial distances conditions, which indicates that our proposed parameter inversion method can predict underground horizontal displacement measurements effectively and robustly for the H-type sensor and the technique is applicable for practical geo-engineering applications.

摘要

地下位移监测是深入岩土体内部进行地下位移测量的一种有效方法。它不仅是地质灾害预测预报的重要手段,也是当前地质灾害监测领域的前沿、热点和复杂课题。在以往的研究中,作者通过将基本电磁感应原理与现代传感技术相结合,设计了一种新型电磁地下水平位移传感器(称为H型传感器),并建立了一种称为基于方程的等效回路法(EELA)的互感电压测量理论模型。在此基础上,本文提出了一种名为“EELA正演建模-近似反演法”的地下位移反演方法。该方法将EELA正演模拟方法与近似优化反演理论相结合,通过对H型传感器进行参数反演来推导地下水平位移。针对对应条件下的水平位移实测值与理论反演值进行了综合对比研究。结果表明,当实测水平位移在0-100mm范围内时,在不同倾斜角度和初始轴向距离条件下,水平位移反演偏差一般检验小于3mm,这表明本文提出的参数反演方法能够有效且稳健地预测H型传感器的地下水平位移测量值,该技术适用于实际的岩土工程应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/15339291412a/sensors-14-09074f13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/b44cca964830/sensors-14-09074f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/bbdf797a498a/sensors-14-09074f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/9bd0142d6af7/sensors-14-09074f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/44d5251a5729/sensors-14-09074f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/521db3380468/sensors-14-09074f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/cbf6c4139fb0/sensors-14-09074f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/2ff71ff88692/sensors-14-09074f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/cfd20b802671/sensors-14-09074f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/30517995ee98/sensors-14-09074f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/b7f08c69edd2/sensors-14-09074f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/78685e911762/sensors-14-09074f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/21036903f0fc/sensors-14-09074f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/15339291412a/sensors-14-09074f13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/b44cca964830/sensors-14-09074f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/bbdf797a498a/sensors-14-09074f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/9bd0142d6af7/sensors-14-09074f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/44d5251a5729/sensors-14-09074f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/521db3380468/sensors-14-09074f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/cbf6c4139fb0/sensors-14-09074f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/2ff71ff88692/sensors-14-09074f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/cfd20b802671/sensors-14-09074f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/30517995ee98/sensors-14-09074f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/b7f08c69edd2/sensors-14-09074f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/78685e911762/sensors-14-09074f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/21036903f0fc/sensors-14-09074f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3423/4063035/15339291412a/sensors-14-09074f13.jpg

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