{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T20:31:26Z","timestamp":1770237086121,"version":"3.49.0"},"reference-count":36,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,3,18]],"date-time":"2020-03-18T00:00:00Z","timestamp":1584489600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61701467"],"award-info":[{"award-number":["61701467"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFC0804604"],"award-info":[{"award-number":["2017YFC0804604"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Research and Development Program of Zhejiang, China","award":["2018C03040"],"award-info":[{"award-number":["2018C03040"]}]},{"name":"Basic Public Welfare Research Program of Zhejiang, China","award":["LGF19F010003"],"award-info":[{"award-number":["LGF19F010003"]}]},{"name":"Natural Science Foundation of Zhejiang Province, China","award":["LY19E070003"],"award-info":[{"award-number":["LY19E070003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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\u20131.5 mm. The combination of structural optimization and measurement method upgrading extends the measurement range of the sensing unit from 0\u201330 mm to 0\u201350 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.<\/jats:p>","DOI":"10.3390\/s20061689","type":"journal-article","created":{"date-parts":[[2020,3,19]],"date-time":"2020-03-19T03:54:14Z","timestamp":1584590054000},"page":"1689","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Research on Structure Optimization and Measurement Method of a Large-Range Deep Displacement 3D Measuring Sensor"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1798-8196","authenticated-orcid":false,"given":"Nanying","family":"Shentu","sequence":"first","affiliation":[{"name":"College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China"}]},{"given":"Sheng","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China"}]},{"given":"Qing","family":"Li","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China"}]},{"given":"Renyuan","family":"Tong","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China"}]},{"given":"Siguang","family":"An","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China"}]},{"given":"Guohua","family":"Qiu","sequence":"additional","affiliation":[{"name":"College of Information Enginerrig, China Jiliang University, Hangzhou 310018, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1033","DOI":"10.1007\/s12303-017-0034-4","article-title":"Landslide prediction, monitoring and early warning: A concise review of state-of-the-art","volume":"21","author":"Chae","year":"2017","journal-title":"Geosci. 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