论文部分内容阅读
在传统遗传算法中融入改进变异算子和小生境运算的改进遗传算法,可更好地保持解的多样性、抑制早熟及较高的收敛速度,并将铲板宽度、铲板倾角和星轮高度作为设计变量,对铲板的装载能力和铲掘力进行多目标优化设计。利用Pro/E、ADAMS、ANSYS进行协同仿真,在ANSYS中加载ADAMS输出的载荷文件,对铲板进行静力学分析,并应用ANSYS中的Fatigue Tool模块对铲板进行了疲劳寿命分析,以此对比优化前后铲板的可靠性。
In the traditional genetic algorithm to improve the mutation operator and niche operation of the improved genetic algorithm, can better maintain the diversity of solutions, inhibit the premature and high convergence rate, and the blade width, blade angle and star wheel Height as a design variable, multi-objective optimization design of the shovel board loading capacity and shoveling force. Using Pro / E, ADAMS and ANSYS to carry out co-simulation, load files output by ADAMS in ANSYS, static analysis of the blade, and fatigue life analysis of the blade by using the Fatigue Tool module in ANSYS Optimize the reliability of the front and rear shovels.