Resumen
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.