ANSYS结合神经网络的干燥机搅拌结构设计与优化OA

To address the fatigue damage and resonance of the stirring structure of the vacuum rake dryer under prolonged high-temperature and material forces,this paper proposes a case-based neural network combined with a multi-objective optimization method.First,five key structural variables including the shaft diameter and the blade inclination angle are selected.With deflection and first-order natural frequency as the objective functions,a multi-objective optimization mathematical model is built.Then,the results during the optimization process are plotted using Matlab to verify the accuracy of the optimization method,and the optimal parameter values are obtained.Both the deflection and the first-order natural frequency after optimization are improved.Finally,the ANSYS simulation software is employed to simulate and verify the data.Results show the error between the optimized values and the simulation values is no more than 2%,proving its effectiveness.This paper may provide some insights into designing the stirring structure of vacuum rake dryers.