Design and development of capacitance based moisture measurement for grains

Tinna, Arpit; Parmar, Nitesh; Bagla, Suraj; Goyal, Deepam; Senthil, Vijayalakshmi

doi:10.1016/j.matpr.2020.11.657

Cited by 6 publications

(5 citation statements)

References 15 publications

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“…There are two methods, direct and indirect, for measuring the moisture content [ 4 , 5 ]. The direct method can be divided into the drying method and chemical method, but it has the disadvantage that it is time-consuming and inefficient [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

The Design and Experimentation of a Corn Moisture Detection Device Based on Double Capacitors

Han,

Wang,

Shi

et al. 2024

Sensors

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Detecting the moisture content of grain accurately and rapidly has important significance for harvesting, transport, storage, processing, and precision agriculture. There are some problems with the slow detection speeds, unstable detection, and low detection accuracy of moisture contents in corn harvesters. In that case, an online moisture detection device was designed, which is based on double capacitors. A new method of capacitance complementation and integration was proposed to eliminate the limitation of single data. The device is composed of a sampling mechanism and a double-capacitor sensor consisting of a flatbed capacitor and a cylindrical capacitor. The optimum structure size of the capacitor plates was determined by simulation optimization. In addition to this, the detection system with software and hardware was developed to estimate the moisture content. Indoor dynamic measurement tests were carried out to analyze the influence of temperature and porosity. Based on the influencing factors and capacitance, a model was established to estimate the moisture content. Finally, the support vector machine (SVM) regressions between the capacitance and moisture content were built up so that the R2 values were more than 0.91. In the stability test, the standard deviation of the stability test was 1.09%, and the maximum relative error of the measurement accuracy test was 1.22%. In the dynamic verification test, the maximum error of the measurement was 4.62%, less than 5%. It provides a measurement method for the accurate, rapid, and stable detection of the moisture content of corn and other grains.

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Section: Introductionmentioning

confidence: 99%

The Design and Experimentation of a Corn Moisture Detection Device Based on Double Capacitors

Han,

Wang,

Shi

et al. 2024

Sensors

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show abstract

“…In another study, Mohan et al [19] proposed a novel approach using capacitive sensors to nondestructively inspect the integrity of food containers. Tinna et al [20] showcased the use of capacitive sensors in determining the moisture content of grains.…”

Section: Introductionmentioning

confidence: 99%

“…Tinna et al. [ 20 ] showcased the use of capacitive sensors in determining the moisture content of grains. When compared to traditional impedance measurement methods, these innovative techniques demonstrated their reliability.…”

Section: Introductionmentioning

confidence: 99%

Rapid assessment of degraded frying oil quality using interdigitated microelectrode capacitive sensors

Thao,

Kien,

Thien

et al. 2023

Euro J Lipid Sci & Tech

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Frying oil is essential in food processing, influencing both the taste and safety of fried foods. However, its quality can deteriorate with repeated use, posing potential risks. Many current methods for evaluating its quality, such as spectroscopic techniques, are time‐consuming and costly. Our study introduces an affordable and rapid device that uses electrical capacitance to assess the quality of frying oil. We developed a capacitive sensor equipped with interdigitated microelectrodes (IEMs) to measure the oil's dielectric constant. After calibrating the sensor's features, we achieved highly precise results. Our design utilized Corel software for drafting and CNC machinery for precise sensor fabrication. In air, the sensor's measurements closely aligned with theoretical predictions, registering an R2 value above 0.7. We identified a correlation between frying frequency and significant shifts in the dielectric constant across three oil samples. Using a signal circuit to adjust the oscillation frequency and a microprocessor for data interpretation, we classified oils into three safety categories: safe, moderate, and risky. Our device provides a cost‐effective and user‐friendly solution to assess frying oil quality, proactively addressing health concerns arising from oil degradation.Practical applications: Our capacitive sensor device can be widely applied in the food industry and restaurants, ensuring the safety and quality of fried products. By using this device, manufacturers and kitchens can make informed decisions about reusing frying oil or replacing it as needed, reducing wasted oil. This cost‐saving device also has the potential to contribute to improving food safety issues.

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“…At present, grain moisture detection methods are divided into offline detection and online detection methods [11]. Offline detection [12] involves removing the water in grain after the test sample is taken from production and processing and calculating the moisture content of the grain through drying or chemical methods, such as the 105 constant weight method [13] and Karl Fischer method [14]. This type of detection is generally used as the comparison standard for detection accuracy but is not practical in the actual production process.…”

Section: Introductionmentioning

confidence: 99%

Design and Experiment of Capacitive Rice Online Moisture Detection Device

Sun

Wan

Che

et al. 2023

Sensors

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To solve the problems of poor stability and low monitoring precision in the online detection of rice moisture in the drying tower, we designed an online detection device for rice moisture at the outlet of the drying tower. The structure of a tri-plate capacitor was adopted, and the electrostatic field of the tri-plate capacitor was simulated using COMSOL software. A central composite design of three factors and five levels was carried out with the thickness, spacing, and area of the plates as the influencing factors and the capacitance-specific sensitivity as the test index. This device was composed of a dynamic acquisition device and a detection system. The dynamic sampling device was found to achieve dynamic continuous sampling and static intermittent measurements of rice using a ten-shaped leaf plate structure. The hardware circuit of the inspection system with STM32F407ZGT6 as the main control chip was designed to realize stable communication between the master and slave computers. Additionally, an optimized BP neural network prediction model based on the genetic algorithm was established using the MATLAB software. Indoor static and dynamic verification tests were also carried out. The results showed that the optimal plate structure parameter combination includes a plate thickness of 1 mm, plate spacing of 100 mm, and relative area of 18,000.069 mm2 while satisfying the mechanical design and practical application needs of the device. The structure of the BP neural network was 2-90-1, the length of individual code in the genetic algorithm was 361, and the prediction model was trained 765 times to obtain a minimum MSE value of 1.9683 × 10−5, which was lower than that of the unoptimized BP neural network with an MSE of 7.1215 × 10−4. The mean relative error of the device was 1.44% under the static test and 2.103% under the dynamic test, which met the accuracy requirements for the design of the device.

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Design and development of capacitance based moisture measurement for grains

Cited by 6 publications

References 15 publications

The Design and Experimentation of a Corn Moisture Detection Device Based on Double Capacitors

The Design and Experimentation of a Corn Moisture Detection Device Based on Double Capacitors

Rapid assessment of degraded frying oil quality using interdigitated microelectrode capacitive sensors

Design and Experiment of Capacitive Rice Online Moisture Detection Device

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