Design and parameters optimization for cutting-conveying mechanism of ramie combine harvester

In order to solve the problems of uneven stubble, low cutting efficiency and frequent breaking and blocking in the cutting and conveying links of ramie combine harvester, a reciprocating double movable blades cutter and a double-layer chain conveyor were designed, and the operating parameter test and optimization were carried out by using the central combination test design theory, with the emphasis on the influence of the forward speed, the cutting speed of the cutter and the conveying speed of the chain on the cutting efficiency, the failure rate and the conveying rate, and the multi-objective optimization was carried out based on these response indicators. Firstly, the structure and operating parameters of the cutting-conveying mechanism of ramie combine were studied. Then, the experiment was designed by the quadratic orthogonal rotation combination test method, and the data is processed by Design-Expert. The regression mathematical model of cutting efficiency, failure rate and conveying rate was established and variance analysis was carried out. By analyzing the effect of interaction of various factors on cutting efficiency, failure rate and conveying rate by response surface methodology, and performing multi-objective optimization on the regression model according to the importance of the optimization target, the optimal combination of the operating parameters of the cutting-conveying parts of the ramie combine harvester was obtained: when the forward speed was 0.85 m/s, the cutting speed was 1.40 m/s, and the chain conveying speed was 1.33 m/s, the cutting efficiency and conveying rate were the maximum and the failure rate was the minimum, with the values of 44.36 plants/s, 93.60% and 4.16%, respectively. The optimized parameters were verified in the field on the ramie combine harvester. In the field test, the cutting efficiency, conveying rate, and failure rate were 43.80 plants/s, 92.45%, and 4.52%, respectively, and the relative errors with the optimized values were 1.3%, 1.2%, and 8.7%, respectively, which was relatively consistent.