Design and Optimization of Working Parts of Vertical Spiral Ditching Machine Based on Milling Force and BP Neural Network Model

Abstract

The existing vertical spiral ditching machine mainly works in flat orchards, and the structural design of ditching components does not match the design of power transmission system, which leads to high ditching power consumption and poor ditching stability. According to the needs of deep application of organic fertilizer in orchards, a spiral cutter was designed to alleviate the common problems of high power consumption and poor stability of ditching machine and reduce the power consumption of ditch cutting. Therefore, the motion parameters and structural parameters of the spiral cutter are optimized. Using ANSYS preprocessor, the finite element model of cutting soil with spiral cutter is established, and the implicit functional relationship between milling force factor and instantaneous cutting thickness is established by using BPNN (BP neural network). On the basis of the established prediction model of milling force, orthogonal experiments were carried out to obtain the best combination of cutter head rotation speed, slotting depth, and advancing speed with minimum power consumption: 20.16 rad/s, 0.3 m, and 0.12 m/s. By investigating the influence of various working parameters on the power consumption of ditching machine, the analysis basis is provided for selecting reasonable working parameters of ditching machine.