## 1 Introduction  
Industrial corn drying plays an important role in improving grain storage, inhibiting the growth of pests and microorganisms, increasing product storage period, and reducing transportation costs [1, 2]. In recent years, the method used to control industrial corn dryers have entered the stage of intelligent control with the development of computer control technology and artificial intelligence [3, 4]. To realize the intelligent control of the grain drying process, modeling the complex drying system with an artificial intelligence algorithm in combination with modern control technology might help to effectively construct an intelligent predictive controller [5]. However, an online corn moisture content measurement device is necessary to provide accurate data samples for establishing a data-driven model of the drying process and for providing accurate feedback information for the dryer controller. Therefore, an in-depth study of online corn moisture content sensor is vital to improving the intelligent control theory of grain drying and to developing intelligent control technology. In recent years, for the moisture content measurement of agricultural products, researchers have developed a variety of static measurement instruments with high measurement accuracy based on optical [6, 7], nuclear [8], hygrometric [9], and dielectric methods [10, 11, 12]. However, due to the difference in drying parameters, environmental conditions, material properties, and development costs, the most practical method is an electronic online measurement device based on the resistance and capacitance properties of materials [13, 14]. Due to the shape of a corn kernel being flat or nearly spherical, the moisture content of different parts in a single kernel varies widely, and water diffusion occurs from the endosperm to the embryo during the drying process [15]. Thus, it is difficult to develop a high-precision online measurement device based on the resistance characteristics of a single grain given the difference in the texture and the dynamic change in the moisture distribution in a single kernel. Since [PERSON]'s research in 1977, [16] showed that a strong correlation exists between grain's dielectric properties and moisture content, various practical applications of moisture content measurement of agricultural products based on their dielectric properties have emerged, such as for flaxseed [17], safflower seeds [18], meat [19], date [20], and hazelnut [21]. The capacitive sensor is a low-cost and easy-to-use method to detect some features of agricultural products according to their dielectric properties. The parallel plate capacitor, designed based on the capacitance method, is a classic and mature application of the capacitance method. For decades, this type of sensor was widely used in quality measurement (especially moisture content measurement) of some agricultural products, having acceptable accuracy. In the grain drying process, a moisture sensor based on the parallel plate structure can accurately and quickly reflect the average moisture content in the drying layer. Porosity is an essential physical parameter that is related to the shape, filling method, size, and distribution of the material; moisture content; storage time; motion state; and many other factors [22]. Considering the porosity change caused by the objective conditions of the drying process, such as the mechanical properties of the grain and the flow characteristics caused by the filling method, the online moisture content measurement devices based on capacitance method still have some defects, such as low precision and poor stability. In the industrial corn drying process, some complex factors, such as the flow of corn [23], harsh external environment [24], and impurities [25], lead to changes in the porosity in the measurement cavity.