The operation of electric rice reaper binders in hilly and mountainous areas currently faces the challenges of poor conveying efficiency and high harvest losses caused by the large dispersion of rice stem posture angles. In this study, we propose a multiparameter collaborative optimization method for improving header structure in an effort to address these challenges. First, key parameters influencing lifting performance and their operational ranges were determined based on a theoretical analysis of the stem-lifting mechanism’s kinematic characteristics. A dynamic model simulating the header’s lifting process was developed by using the ADAMS multibody dynamics platform. Subsequently, we designed a quadratic regression orthogonal rotation combination experiment with three factors, i.e., the stem-lifting speed ratio coefficient, the cutter installation position, and the header tilt angle, using the stem-lifting angle as the evaluation metric. The variance in the experimental data was analyzed with Design-Expert 13.0, and response surface methodology (RSM) was applied to elucidate the parameter interaction effects. The optimal parameter combination was identified as a speed ratio coefficient of 2.14, a cutter installation position of 258.79 mm, and a header tilt angle of 62.63°, yielding a theoretical stem-lifting angle of 2.36°. Field validation tests demonstrated an actual stem-lifting angle of 2.44° (relative error: 3.39%) and a header loss rate of 0.59%, representing a 49.6% reduction compared with the pre-optimized design. These results confirm that the optimized header satisfies operational requirements for hilly terrain rice harvesting, providing both theoretical guidance and technical advancements for the design of low-loss harvesting machinery.

Blade cutters are a component in paddy field pulping machines that perform mud splashing, and the design of their structural and motion parameters will directly affect the splashed-mud volume and pulping-machine efficiency. Therefore, the optimization of the blade cutter’s structural and motion parameters is an important approach for improving the operating performance of paddy field pulping machines. In this study, based on the central-composite-design (CCD) method and a response-surface-method-based variance analysis, a regression-forecast model for the relationship between the splashing performance of the blade cutter and the blade’s structural and motion parameters was constructed to determine the influence of these parameters on the multi-dimensional splashing performance of blade cutters. Additionally, with the construction of a multi-objective performance-optimization model for pulping-machine blade cutters, the predicted optimal structural and motion parameters could be obtained based on the genetic algorithm. The ideal operating performance could be achieved when the blade turning radius was 180 mm, with a bending angle of 125°, a sub-cutter dip angle of 63°, a forward velocity of 0.15 m/s, and a rotating speed of 158 r/min. Verification of the optimization results in a bench test showed that the mean relative errors between the theoretical and experimental values of the mud volume and power consumption were 9.13% and 8.86%, respectively, revealing the high accuracy of the mud-volume and power-consumption models. Furthermore, there was a significant reduction in blade-cutter unit power consumption of 19.13%. These research results can provide a theoretical reference and technical support for blade-cutter optimization and improving pulping-machine performance.

The knotter, as a core module for the knotting function of a rice electric binder, has structural parameters and spatial configurations that significantly impact the efficiency and quality of rice collection, making the in-depth analysis and optimization of these parameters, and their spatial relationships, crucial for enhancing the operational quality of the rice electric binder. At present, rice binders still face the issues of a low bundling efficiency and quality, which affect the progress of rice harvesting during the harvest season. Through theoretical analysis and calculation, this study determined the main parameters affecting the knotter’s knotting process and their value ranges. Based on the ADAMS software, a simulation model of the knotter operation was constructed. Using the Box–Behnken design (BBD) method and response surface analysis of variance, a regression prediction model for knotter operation evaluation indicators was established, and the multi-objective optimization of the knotter’s operation quality was performed. The prediction results showed that, under the optimal structural parameter combination of a 30.23° angle between the knotting pincer and rope guard axes, a −3.75 mm rope clamping board position, and a 40.75° inclination angle of the knotting pincer convex platform, the knotter’s knotting quality reached the best state, with an average knot end protrusion of 9.10 mm and a maximum tension of 134.25 N on the knotting rope. The field tests results showed an average knot end protrusion of 9.60 mm and a maximum tension of 127.87 N on the knotting rope, with average relative errors of 5.82% and 4.72% compared to the theoretical values, respectively. After optimizing the knotter, the average knot end protrusion increased by 14.48% and the maximum tension of the knot rope was reduced by 11.27%. Meanwhile, the knotter achieved an average bundling rate as high as 99.3%. The bundling success rate also increased by 2.7%. These results fully verify the reliability and accuracy of the regression model, and demonstrate the reasonableness of the knotter structural parameter optimization design, providing a theoretical basis and reference for improving the operational quality of the rice electric binder.

To improve the distribution of mud particles collected in the tray during the operation of paddy field mud spreader blades, the optimal combination of parameters for the blades that results in the best uniformity of mud dispersion needs to be identified. In this study, a thorough force analysis was conducted on the spreading process, and computational equations were formulated to describe the motion of mud particles. By utilizing the discrete element simulation technique, a simulation model was developed to accurately represent the intricate interaction between the blades and mud particles. Through the single-factor simulation experiments, the ranges of key parameters such as the rotation radius, bending angle, sub-blade tilt angle, forward velocity, and rotational speed of the blade were determined. A secondary orthogonal rotational combination design was employed to establish a regression prediction model between the non-uniformity of mud dispersion and the key blade parameters. Subsequently, a multivariate single-objective optimization method was used to develop an optimization model for the non-uniformity of mud dispersion. The results indicate that the hierarchical order of factors influencing the non-uniformity of mud dispersion is as follows: rotation radius > rotation speed > bending angle > forward velocity > sub-blade tilt angle. To achieve a minimum spreading non-uniformity of 29.63%, a specific configuration is required, which includes a blade rotation radius of 188 mm, a bending angle of 121°, a sub-blade tilt angle of 30°, a forward velocity of 400 mm/s, and a rotation speed of 191 r/min. Finally, the accuracy of the optimization results was verified by means of bench tests. The research results provide a crucial reference for enhancing the uniformity of mud dispersion in paddy field mud spreader blades.