Application of neural network approximate model in lightweight design of hydraulic support top beam
WANG Bangxiang
LU Jingui
WANG Jingtao
QIAN Peng
Abstract：For the top beam of hydraulic support to meet the requirements of working conditions,the goal of the project is to minimize the quality.A lightweight design method for the top beam was proposed combined with neural network approximation model and genetic algorithm.Firstly,using ANSYS to build a parametric model to the top beam,taking the quality of the top beam as the objective function,5 design variables that affect quality and intensity were selected,the optimization model of the top beam was established.Then,Optimal Lat-in Hypercube sampling method and ANSYS were used to get training samples.Neural network was applied to nonlinear fitting of sample set,and the approximate model of neural network was established.The approximate model was used to approximate the quality and maximal stress of the top beam,genetic algorithm was applied to solve the optimization model of the top beam,and the optimal solution was obtained finally.The optimization results showed that the quality of the top beam was 8 038.2 kg,which reduced by 9.66%.The maximum stress value was less than the yield strength of the top beam material and met the fatigue life requirement.
Keywords：hydraulic support top beamneural networkapproximate modelgenetic algorithmlightweight design
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 87-94 )