Title
Research on Structure Optimization and Measurement Method of a Large-range Deep Displacement 3D Measuring Sensor.
Abstract
Deep displacement monitoring of rock and soil mass is the focus of current geological hazard research. In the previous works, we proposed a geophysical deep displacement characteristic information detection method by implanting magneto-electric sensing arrays in boreholes, and preliminarily designed the sensor prototype and algorithm of deep displacement three-dimensional (3D) measurement. On this basis, we optimized the structure of the sensing unit through 3D printing and other technologies, and improved the shape and material parameters of the permanent magnet after extensive experiments. Through in-depth analysis of the experimental data, based on the data query algorithm and the polynomial least square curve fitting theory, a new mathematical model for 3D measurement of deep displacement has been proposed. By virtue of it, the output values of mutual inductance voltage, Hall voltage and tilt measuring voltage measured by the sensing units can be converted into the variations of relative horizontal displacement, vertical displacement and axial tilt angle between any two adjacent sensing units in real time, and the measuring errors of horizontal and vertical displacement are tested to be 0-1.5 mm. The combination of structural optimization and measurement method upgrading extends the measurement range of the sensing unit from 0-30 mm to 0-50 mm. It shows that our revised deep displacement 3D measuring sensor can better meet the needs of high-precision monitoring at the initial stage of rock and soil deformation and large deformation monitoring at the rapid change and imminent-sliding stage.
Year
DOI
Venue
2020
10.3390/s20061689
SENSORS
Keywords
DocType
Volume
geological disaster,deep displacement monitoring,horizontal displacement,vertical displacement,mathematical modeling,contour
Journal
20
Issue
ISSN
Citations 
6
1424-8220
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Nanying Shentu101.01
Wang Sheng285.80
Qing Li313143.14
Renyuan Tong401.01
Siguang An500.34
Guohua Qiu600.34