Capacitive Online Corn Moisture Content Sensor Considering Porosity Distributions: Modeling, Design, and Experiments

• Main Authors: Chengjie Li, Xuefeng Zhang, Mingang Meng, Bin Li, Changyou Li
• Format: Article
• Language: English
• Published: MDPI AG 2021-08-01
• Series: Applied Sciences
• Subjects: corn; moisture sensor; online measurement; industrial drying; porosity
• Online Access: https://www.mdpi.com/2076-3417/11/16/7655

An online corn moisture content measurement device would be a key technology for providing accurate feedback information for industrial drying processes to enable the dynamic tracking and closed-loop control of the process. To overcome the problem of large measurement error caused by the characteristics of the corn flow state and the pore distribution when a parallel plate capacitor is applied to the online moisture content measurement process, in this study, we summarized the constraint conditions of the sensor’s structure parameters by mathematical modeling and calculated the optimal sensor design size. Moreover, the influence of porosity variation on moisture content measurement was studied by using the designed sensor. In addition, a mathematical model for calculating corn moisture content was obtained for the moisture content range of 14.7% to 26.4% w.b., temperature of 5 °C to 35 °C, and porosity of 38.4% to 44.6%. The results indicated that the fluctuation in the online moisture content measurement value was obviously reduced after the porosity compensation. The absolute error of the measured moisture content value was −0.62 to 0.67% w.b., and the average of absolute values of error was 0.32% w.b. The main results provide a theoretical basis and technical support for the development of intelligent industrial grain–drying equipment.