郭文川, 宋克鑫, 张 鹏, 韩文霆. 土壤温度和容重对频率反射土壤水分传感器测量精度的影响[J]. 农业工程学报, 2013, 29(10): 136-143.
    引用本文: 郭文川, 宋克鑫, 张 鹏, 韩文霆. 土壤温度和容重对频率反射土壤水分传感器测量精度的影响[J]. 农业工程学报, 2013, 29(10): 136-143.
    Guo Wenchuan, Song Kexin, Zhang Peng, Han Wenting. Effects of temperature and bulk density on measurement precision of soil moisture sensor based on frequency domain reflectometry[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2013, 29(10): 136-143.
    Citation: Guo Wenchuan, Song Kexin, Zhang Peng, Han Wenting. Effects of temperature and bulk density on measurement precision of soil moisture sensor based on frequency domain reflectometry[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2013, 29(10): 136-143.

    土壤温度和容重对频率反射土壤水分传感器测量精度的影响

    Effects of temperature and bulk density on measurement precision of soil moisture sensor based on frequency domain reflectometry

    • 摘要: 为探究土壤温度和容重对FDR(频率反射)含水率测量结果的综合影响规律,以陕西杨凌地区的塿土为研究对象,以基于FDR技术的电流型DSW-T2型土壤温湿度传感器为测量仪器,研究了土壤的含水率(3.82%~21.43%)、容重(0.91~1.30 g/cm3)和温度(2.5~50℃)对传感器输出信号的影响;建立了传感器的输出电流与土壤含水率、容重和温度的综合测量数学模型,实验分析了模型在预测含水率方面的可行性。结果表明,传感器的输出电流随土壤含水率、温度和容重的增大而增大,可用三元二次方程表示输出电流与土壤含水率、温度和容重之间的关系;在0.05的显著水平上,含水率、温度和容积密度均对模型有显著影响。基于模型的计算输出电流与实际输出电流的绝对误差范围是-1.167~1.216 mA,计算含水率与实际含水率的绝对误差范围是-2.638%~2.812%。本研究对于开发具有温度和容积密度补偿功能的新型FDR土壤含水率传感器的综合测量模型有指导作用。

       

      Abstract: Abstract: Moisture content of soil is helpful for water-saving irrigation. Soil moisture sensors using frequency domain reflectometry (FDR) are more and more popular in market. Soil temperature is a major factor affecting moisture measurement precision. So it has been widely considered in developing FDR soil moisture sensor. However, volume density, which is also a major factor influencing measurement precision of soil moisture, has been considered hardly. To investigate the comprehensive influence of temperature and volume density on moisture content by FDR moisture sensor, Lou soil in Yangling region, Shaanxi Province, were used as samples , and DSW-T2 soil temperature and moisture sensor (current output type) using FDR technology, was used as instrument to study the influence of moisture content at seven levels (3.82%, 7.58%, 9.29%, 11.65%, 14.87%, 18.61%and 21.43% in wet basis), volume density at five levels (0.91 g/cm3, 1.00 g/cm3, 1.09 g/cm3, 1.21 g/cm3 and 1.30 g/cm3) over temperature range from 2.5℃ to 50℃ at 2.5℃ interval on output current. DM6801 digital temperature sensor was used to measure soil temperature and to detect precision of DSW-T2 on temperature measurement. A comprehensive mathematical model between output current, moisture content, volume density and temperature was established. Newton iteration method was applied to predict moisture content under laboratory conditions. The model's feasibility in predicting moisture content from 3.82%~21.43% and volume density from 0.91g/cm3-1.30g/cm3 at 2.5-50℃ was verified. The results indicated that the output current of DSW-T2 increased with increasing moisture content, volume density and temperature over the investigated range of each factor. The absolute error between calculated temperature from obtained output current of DSW-T2 and measured one using DM6801 was within -3.8%-10.7%. The absolute error between calculated moisture content by output current of DSW-T2 and measured one by oven-drying method was -2.2℃-2.4℃. A quadratic model with three-degree of freedom could be used to describe the relationship between output current of DSW-T2 and moisture content, volume density and temperature of soil. At 0.05 significant level, soil moisture content, temperature and volume density had significant effect on the model. The absolute error between calculated output current and measured one was between -1.167-1.216mA. The absolute error between calculated moisture content and actual one was within -2.638%-2.812% when the output current, temperature and volume density were given. By comparing the moisture content obtained by DSW-T2 soil temperature and moisture sensor with out volume density information and calculated one by the regressed three-degree model considering the volume density, it showed that considering volume density is helpful to improve moisture measurement precision. The study offers useful information on developing a comprehensive measurement model for FDR soil moisture sensor with temperature and volume density compensation functions.

       

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