Temperature compensation in a low cost frequency domain (capacitance based) soil moisture sensor

Oates, Martin J.; Fernández-López, Antonio; Ferrández-Villena, Manuel; Ruiz-Canales, A.

doi:10.1016/j.agwat.2016.11.002

Cited by 23 publications

(19 citation statements)

References 25 publications

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“…The application of the TDR technique and the introduction of temperature correction ensures that soil moisture can be determined with high accuracy (up to 0.001 m 3 m -3 ). The method of determination of the temperature correction is elucidated in the papers by (Janik et al, 2014;Oates et al, 2017;Skierucha, 2009). When the LP/ms probe is placed horizontally, we found that it was possible to register the volume of soil moisture in the top soil layer (2 cm).…”

Section: Methodsmentioning

confidence: 95%

Atmospheric water infiltration intensity in non-rainfall periods under conditionsof varied soil moisture

Dawid¹,

Janik²

2018

International Agrophysics

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The paper presents a function-type relation which demonstrates that volumetric moisture of the surface horizon of soil has an effect on the intensity of atmospheric water infiltration during non-rainfall periods. The relation, developed and then verified on the basis of independent material, reveals that the intensity of infiltration decreases with an increase in volumetric moisture of soil. For the case presented herein, infiltration ceases when volumetric moisture is higher than 0.15 m3 m−3. The developed function also takes into account the effect of atmospheric conditions through the introduction of another argument into the domain. The aforementioned is in the form of potential condensation efficiency measured on a dew collector, and assumes the form of a modified logistic function.

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Section: Methodsmentioning

confidence: 95%

Atmospheric water infiltration intensity in non-rainfall periods under conditionsof varied soil moisture

Dawid¹,

Janik²

2018

International Agrophysics

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“…A mathematical model of nonlinear adjustment can overcome the shortcomings of conventional sensors, and to a large extent, reflect and compensate the complex effect of temperature on moisture readings [9][10][11]. However, the existing compensation methods often use nonlinear mathematical models with fixed orders, which may not reach optimal error under different usage environments, thus making it difficult to attain the best compensation effects.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Nonlinearity Compensation System for Integrated Temperature and Moisture Sensor

Chen

Zhou

et al. 2019

Micromachines

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Measuring temperature and moisture are important in many scenarios. It has been verified that temperature greatly affects the accuracy of moisture sensing. Moisture sensing performance would suffer without temperature calibrations. This paper introduces a nonlinearity compensation technique for temperature-dependent nonlinearity calibration of moisture sensors, which is based on an adaptive nonlinear order regulating model. An adaptive algorithm is designed to automatically find the optimal order number, which was subsequently applied in a nonlinear mathematical model to compensate for the temperature effects and improve the moisture measurement accuracy. The integrated temperature and moisture sensor with the proposed adaptive nonlinear order regulating nonlinearity compensation technique is found to be more effective and yield better sensing performance.

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“…There needs to construct a temperature-related nonlinear model to compensate the influence of temperature. The dielectric permittivity of water decreases with increasing temperature [4,11,12], therefore the temperature-related nonlinearity can be assumed by where real ðiÞ and is the real moisture of the i th test. " b;real ðiÞ is the real dielectric permittivity of water, while Cði; T Þ is temperature-related nonlinear factor, and a m ðiÞ, m ¼ 1; 2; 3 are the nonlinear coefficients to be estimated.…”

Section: Nonlinear Modelling and Coefficients Estimationmentioning

confidence: 99%

“…And also the nonlinearity changes violently with the variation of temperature conditions [3]. Thus, it's difficult to calibrate the temperature dependent nonlinear characteristics of moisture sensor [4].…”

Section: Introductionmentioning

confidence: 99%

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An integrated moisture and temperature sensor with model based temperature-dependent nonlinearity compensation

Chen

Zhou

Huang

2018

IEICE Electron. Express

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Moisture sensors have been widely implemented in agricultural and forestry applications, but they can not obtain satisfied sensing performance without calibration. This letter presents an integrated moisture and temperature sensor with a model based linearization for eliminating the temperature-dependent nonlinearity. The temperature related nonlinear model is built by analyzing the relationship between the real moistures and the pairs of measured moistures and temperatures. The least squares algorithm is applied to estimate the coefficients of the obtained nonlinear model. The proposed linearization system has the advantage of wide suitability and applicability, and its performance is validated by experimental results.

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Temperature compensation in a low cost frequency domain (capacitance based) soil moisture sensor

Cited by 23 publications

References 25 publications

Atmospheric water infiltration intensity in non-rainfall periods under conditionsof varied soil moisture

Atmospheric water infiltration intensity in non-rainfall periods under conditionsof varied soil moisture

Adaptive Nonlinearity Compensation System for Integrated Temperature and Moisture Sensor

An integrated moisture and temperature sensor with model based temperature-dependent nonlinearity compensation

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