Lightweight design of excavator working device based on automatically generated surrogate model

Abstract

Abstract To address the conservative excavator working device configuration obtained by traditional design methods, a lightweight structure design method was proposed in this study based on automatically generated surrogate model. A finite element model of the working device was first constructed, and its accuracy was verified against experimental results. By incorporating the Gini coefficient to compute the information entropy pertaining to the relationship between variables and responses, the entropy-weighted TOPSIS method has been significantly enhanced. Subsequently, the comprehensive contributions of the boom design parameters to the mass, deformation, and stress responses were calculated, and the parameters exerting significant effects were selected as the design variables through the application of the improved TOPSIS. Next, the working device optimisation model was subsequently established using the minimum mass as the target and the stress and deformation as constraints. And then, a surrogate model of the working device was constructed using 500 sample points. Finally, a genetic algorithm was employed to derive a lightweight design of the excavator boom based on the surrogate model. The results indicate that the proposed method reduced the weight of the considered hydraulic excavator boom by 9.30%; further, a finite element simulation verified that the stress and deformation met the design requirements of the boom.

Keywords

• Size optimisation
• Design optimisation
• Maximum decision coefficient
• Boom
• The improved TOPSIS