Data-Driven Calibration of Soil Moisture Sensor Considering Impacts of Temperature: A Case Study on FDR Sensors

被引：14
作者：
Chen, Liping [1 ,2 ]
Zhangzhong, Lili [1 ,2 ]
Zheng, Wengang [1 ,2 ]
Yu, JingXin [1 ,2 ]
Wang, Zehan [3 ]
Wang, Long [3 ,4 ]
Huang, Chao [3 ,4 ]
机构：
[1] Natl Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China
[2] Minist Agr, Key Lab Qual Testing Hardware & Software Prod Agr, Beijing 100097, Peoples R China
[3] Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing 100083, Peoples R China
[4] Inner Mongolia Univ Technol, Key Lab Wind Energy & Solar Energy Technol, Minist Educ, Hohhot 010051, Peoples R China
来源：
SENSORS | 2019年 / 19卷 / 20期
基金：
国家重点研发计划; 中国国家自然科学基金;
关键词：
calibration; data-driven; impacts of temperature; soil moisture sensor; WATER-CONTENT;
D O I：
10.3390/s19204381
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
Commercial soil moisture sensors have been widely applied into the measurement of soil moisture content. However, the accuracy of such sensors varies due to the employed techniques and working conditions. In this study, the temperature impact on the soil moisture sensor reading was firstly analyzed. Next, a pioneer study on the data-driven calibration of soil moisture sensor was investigated considering the impacts of temperature. Different data-driven models including the multivariate adaptive regression splines and the Gaussian process regression were applied into the development of the calibration method. To verify the efficacy of the proposed methods, tests on four commercial soil moisture sensors were conducted; these sensors belong to the frequency domain reflection (FDR) type. The numerical results demonstrate that the proposed methods can greatly improve the measurement accuracy for the investigated sensors.
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页数：11
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