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基于电容传感器的非侵入式土壤水分估算的实验室研究。

A Laboratory Study on Non-Invasive Soil Water Content Estimation Using Capacitive Based Sensors.

机构信息

Department of Infrastructure Engineering, School of Engineering, The University of Melbourne, Parkville, VIC 3010, Australia.

出版信息

Sensors (Basel). 2019 Feb 5;19(3):651. doi: 10.3390/s19030651.

Abstract

Soil water content is an important parameter in many engineering, agricultural and environmental applications. In practice, there exists a need to measure this parameter rather frequently in both time and space. However, common measurement techniques are typically invasive, time-consuming and labour-intensive, or rely on potentially risky (although highly regulated) nuclear-based methods, making frequent measurements of soil water content impractical. Here we investigate in the laboratory the effectiveness of four new low-cost non-invasive sensors to estimate the soil water content of a range of soil types. While the results of each of the four sensors are promising, one of the sensors, herein called the "AOGAN" sensor, exhibits superior performance, as it was designed based on combining the best geometrical and electronic features of the other three sensors. The performance of the sensors is, however, influenced by the quality of the sensor-soil coupling and the soil surface roughness. Accuracy was found to be within 5% of volumetric water content, considered sufficient to enable higher spatiotemporal resolution contrast for mapping of soil water content.

摘要

土壤含水量是许多工程、农业和环境应用中的一个重要参数。在实践中,需要在时间和空间上相当频繁地测量这个参数。然而,常见的测量技术通常具有侵入性、耗时、费力,或者依赖于潜在危险(尽管受到高度监管)的基于核的方法,这使得频繁测量土壤含水量变得不切实际。在这里,我们在实验室中研究了四种新的低成本非侵入式传感器估计一系列土壤类型的土壤含水量的有效性。虽然这四种传感器的结果都很有希望,但其中一种传感器,称为“AOGAN”传感器,表现出了卓越的性能,因为它是基于结合其他三种传感器的最佳几何和电子特性设计的。然而,传感器的性能受到传感器-土壤耦合和土壤表面粗糙度的质量的影响。结果发现,传感器的准确性在体积含水量的 5%以内,这足以实现更高时空分辨率的对比度,用于绘制土壤含水量图。

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