基于神经网络的挖掘机斗杆结构应力约束模型

针对挖掘机斗杆结构智能优化过程中，采用ANSYS有限元软件进行应力约束处理的效率低，结构应力等强度化控制难度大，未能实现最大限度的省材等问题，提出一种基于应力普查的挖掘机斗杆结构智能优化应力约束模型。通过多工况斗杆结构应力普查法，确定可准确表征斗杆结构应力分布状况的应力特征截面，建立斗杆特征截面神经网络应力预测模型。本文，以中小型挖掘机耳板分离式斗杆结构为例，构建基于应力普查的斗杆应力约束模型，实现斗杆结构应力约束，提高斗杆结构优化速率。

Stress Constraint Model based on Neural Networks for Excavator Stick Structural Intelligent Optimization

In allusion to the deficiencies existing in current stress constraint processed by ANSYS software for excavator stick structural intelligent optimization such as the inefficiency in handling the stress constraint, the difficulty in realizing the stress intensity control and maximum material economized of stick, the stress constraint model based on stress intensity for stick structural intelligent optimization is put forward. The stress character sections which can represent the distribution of stress were determined by stress investigation, then, establishing the neural network model of stress for stick. Excavator ear-plate stick is taken as an example to illustrate the es?tablishment of the stress constraint model and demonstrate the constraint model can effectively achieve the stress constraint of stick structure, thus, improve the rate of stick structural intelligent optimization.