Design and modelling of the full-feed peanut picking device with self-adaptive adjustable working clearance and feeding rate.

To improve the declining performance of a full-feed peanut picking device or solve the mechanical failures that occur due to fluctuations in the feeding rate during operation, the 4HLJI-3000 peanut intelligent picking combine harvester, which is a picking device with a self-adaptive adjustment of the working clearance, was developed as the research object in this study. Moreover, the key components, such as the picking roller, concave plate sieve and clearance adjustment mechanism of the concave plate sieve, were designed and analysed. Through the force analysis of the concave plate sieve of the picking device, the mathematical model of the concave plate sieve displacement of the picking device and feeding rate was obtained. The software system for monitoring, storing and analysing the concave plate sieve displacement of the picking device based on EasyBuilder Pro was designed, and the road monitoring test of displacement variation of concave plate sieve of the picking device and feeding rate was carried out. The linear function, power function, exponential function, quadratic function, compound function, logarithmic function and cubic function fitting were used to perform regression analysis of the test results by using IBM SPSS software. The results showed that the cubic function model had a higher fitting precision, and its determination coefficient was 0.992. Model verification experiments were proposed, and the results showed that the established cubic function model had a good accuracy. The absolute deviation rate ranged from 0 to 4.83%, and the average deviation rate was 2.22%. The deviation rate increased with an increasing feeding rate. The field experiments also proved that there was a cubic function relationship between the feeding rate and concave plate sieve displacement, the measured concave plate sieve displacement deviation rate ranged from 0 to 6.19%, and the average deviation rate was 2.73% compared with the calculated results. This study can provide a reference for the optimization design of the structure of full-feeding picking devices for peanuts and other crops and the intelligent measurement and control of the feeding rates. [ABSTRACT FROM AUTHOR]