Grain Sieve Loss Fuzzy Control System in Rice Combine Harvesters

Model Study on the Combination of Operating Parameters of Corn Kernel Harvesters

This study analyzed the engine operating condition curve of the corn kernel harvester. Field experiments identified the feed rate, concave clearance, and cylinder speed as the main factors affecting operating quality and efficiency. A ternary quadratic regression orthogonal center-of-rotation combined optimization test method was used to determine the feed rate, cylinder speed, and concave clearance as the influencing factors, and the engine speed variation rate, crushing rate, impurity rate, loss rate, and cylinder speed variation rate as the objective functions. A mathematical regression model was developed for the combination of operating quality indicators, efficiency indicators, and operating parameters of the corn kernel harvester. A non-linear optimization method was used to optimize the parameters of each influencing factor. The results showed that with a feed rate of 12 kg/s, a forward speed of 5 km/h, a cylinder speed of 360 r/min, and a concave clearance of 30 mm, the average crushing rate was 3.91%, the average impurity rate was 1.71%, and the kernel loss rate was 3.1%. This model could be used for the design and development of intelligent control systems.

Application of Fuzzy Logic for Controlling Spray Drying Parameters in Production of Bignay (Antidesma Bunius) Juice Powder

Spray drying is a rapid, continuous, cost-effective, reproducible, and scalable process for reducing the moisture content of a fluid material into a solid powder. To improve this process in juice powder production, automation can be applied to increase efficiency and productivity. Hence, fuzzy logic is used in this study as a control system in the spray-drying process of concentrated liquid bignay juice into juice powder, where the inlet temperature and carrier agent concentrations affecting the properties of the juice powder, such as moisture content and product yield, are considered. The proposed fuzzy system can provide feedback to the control variables, inlet temperature, and carrier agent concentration based on the moisture content and product yield of the juice powder.

Development and Experimental Analysis of a Fuzzy Grey Control System on Rapeseed Cleaning Loss

One of the most important means of improving the mechanization of rapeseed harvests and increasing farmers’ income is to reduce the cleaning loss of rapeseed. In this study, a fuzzy grey control system was developed using an assembled cleaning loss sensor. Based on experimental data, the relationship between the cleaning loss and the opening of the louver sieve in the cleaning device was obtained. The fuzzy control scheme was established by combining grey prediction and the fuzzy control principle. Secondly, a microcontroller unit (MCU) was used as the controller, and the opening of the louver sieve was automatically regulated by detecting the signal of the cleaning loss. Finally, the performance and robustness of the control system was evaluated in field tests. Different experiments were conducted under different speed conditions to reflect the variable throughput. Results showed that using the grey prediction control system can realize the adjustment of the louver sieve opening in real time. The cleaning loss could be maintained within the ideal setpoint interval, compared with the operation with the control system switched off. These findings indicate that the application of the grey fuzzy control system reduces cleaning loss, and the nonlinear, time-variable and time delay problems in cleaning devices can be solved effectively.