Design and simulation of capacitive sensor for grain moisture detection

The high moisture content of grain would result in quality deteriorations such as mold and mildew during storage and transportation. For effective detection of grain moisture, a forked-finger capacitive sensor in the form of triangular prism is proposed. The effect of the sensor structural parameters on its capacitance, electric field distribution, sensitivity and penetration depth are investigated using finite element simulations. The results show that an optimised effective penetration depth of 2.73 mm for grain moisture detection can be achieved when the finger width, number, length and spacing are 50 μm, 25.4 mm and 50 μm, respectively. This work may provide a new approach for the structural design of capacitive grain moisture sensors.


Introduction
Traditional agriculture has been moving toward mechanization and sophistication with the continuous development of science and technology, and the safety of grain has become an important concern.The control of grain moisture is critical to many processes such as production and marketing.For instance, grain can become moldy if its moisture content is high during storage and transportation [1].Conversely, if the moisture content of the grain is too low, the quality of the grain will suffer [2].As a result, rapid and non-destructive detection of the moisture content of grain is one of the current priorities in the field of grain preservation.
In this paper, the capacitive moisture sensor combining triangular prism structure with forked finger electrodes is proposed for grain moisture sensing.The influence of the sensor structure on the electric field distribution, capacitance, and sensitivity is analyzed, and an optimal design of the sensor structure is completed.

Detection principle of grain moisture sensor
Grains are dielectric substances between conductors and insulators, and the moisture content is an important factor that affects the dielectric properties of grains.Therefore, it is feasible to perform non-destructive detection of the moisture content of grains using the dielectric parameters.The moisture content of the grain can be calculated by placing the capacitive sensor into the grain and measuring the capacitance value, as shown in Figure 1(a).
To achieve accurate grain moisture measurements, the sensor needs to have good sensitivity and sufficient penetration depth.For conventional planar fork-finger capacitors, the electric field mainly distributes in the plane between the fingers and is less sensitive to changes in the dielectric constant of grain above the electrodes.Therefore, the capacitive sensor combining triangular prism structure with forked finger electrodes is designed, as shown in figure 1(b).The triangular prism structures would enhance the spatial electric field distribution between the electrodes (figure 1(c)), increase the penetration depth as well as the sensitivity to the changes of grain moisture above the sensor.

Structure of fork-finger capacitive sensor
The sensitivity of fork-finger capacitive sensor depends on its structure.The capacitance value depends on the geometrical parameters of electrodes, thickness of the dielectric material, and dielectric properties, etc.In our design, the sensor contains front detection electrodes and back shielding electrodes.The detection electrodes are in the same plane with a triangular shape on the cross section.Figure 2 shows the schematic cross section and parameters of the sensor, where h1 is the thickness of the substrate layer, h2 is the thickness of the buried oxygen layer, h3 is the thickness of the device layer, h4 is the thickness of the glass, d1 is the thickness of the sensitive fork finger, w1 is the width of the sensitive fork finger, t1 is the spacing of the sensitive fork finger, N1 is the number of sensitive fork

Mathematical modeling
Finite element data calculation is used for analyzes because the design parameters of capacitive grain moisture sensors are complex.The sensitivity of sensor is affected by the variation of structural parameters, and it is difficult to analyze the electric field distribution using traditional theoretical analysis methods [3].According to the differential form of the classical Maxwell equations, it should be generated as: where D is the electric flux density; B is the magnetic induction strength.The internal electromagnetic field of a capacitive sensor can be considered as a stable electrostatic field [4], and the solution of the three-dimensional electrostatic field satisfies Poisson's equation: In the finite element simulation for the case where there is no free charge in the measuring region of the sensor, the electric field in the vicinity can be expressed by: (3) Where ε0 is the dielectric constant in a vacuum environment, εr(x,y) is the relative distribution function of the dielectric constant of the medium; Φ(x,y) is the potential distribution function; • and are the gradient and gradient operators.The capacitance value of the measurement region after determining the boundary conditions can be obtained as follows: Where Q is the electrode plate charge and U is the voltage applied to the excitation electrode; Ω is the integration region; and D is the potential shift vector.

3.Results and Discussion
Figure 4 shows the effect of structural parameters on the capacitance value of sensor.Changes in grain moisture were simulated by varying the relative dielectric constants.The results show that the capacitance value increases continuously with increasing fork finger width, number of fork fingers and fork finger length, and increases with decreasing fork finger spacing.Figure 5 shows the rate of change of the output capacitance value with the relative permittivity of the grain, and the sensitivity S of the capacitive sensor is defined as follows: The capacitive sensitivity increases with the increase of fork finger width, fork finger number and fork finger length, and increases with the decrease of fork finger spacing until it stabilizes.Based on the simulation results, the optimized structural parameters were obtained, and the suggested design dimensional parameters are as follows: fork finger width = 50 μm, number of fork fingers = 25, fork finger length = 4 mm, and fork finger spacing = 50 μm.The simulation results show that the sensitivity of the prepared capacitive sensor is about 0.69 pF, and the penetration depth can reach 2.73 mm.

Conclusions
In this paper, a grain moisture capacitive sensor with triangular-prism-structrured fork finger electrodes is designed, and the influence of the sensor structure parameters on the sensing performance are investigated.The simulation results show that the capacitance value and the capacitance sensitivity of the sensor increase with the increase of the finger width, the number of fingers and the finger length, and decrease with the increasing of finger distance.The sensitivity of the prepared sensor is about 0.69 pF and the detection depth is about 2.73 mm, which can realize the non-contact measurement between the sensor and the grain.Our work may provide a new approach for the structural design of capacitive sensors that feasible to detect the moisture content of grain.

Figure 1 .
Figure 1.Capacitive sensor for grain moisture detection: (a) Schematic of grain moisture detection; (b) Structure of the sensor; (c) Electric field distribution between electrodes.

Figure 2 .
Figure 2. Schematic cross section and parameters of the sensor.

Figure 3 .
Figure 3.The simulation results of FEM: (a) the model structure; (b) electric potential distribution; (c) electric field vector distribution.