摘要
臂架结构尺寸的大小,对起重机的经济性和安全性起着重要的作用。本文首先对臂架结构进行参数化设计,然后利用粒子群优化算法进行优化设计,但在应用过程中,该算法较易陷入局部最优解。为此,引进模拟退火算法,对粒子群算法进行"扰动",当判断粒子群算法陷入局部最优解后,能够跳出,继续寻找全局最优解。结果表明:该组合算法对臂架结构优化收敛速度显著,具有较好的工程应用价值。
The size of structural dimensions of the jib plays an important role in the economy and security of the crane. First of all, the parametric design was used to develop the jib. Then the particle swarm optimization algo- rithm was used to optimize the design of the crane jib. However,in the application process,the algorithm is easy to fall into local optimal solution. In order to overcome these disadvantages, the particle swarm algorithm was ＂disturb- anced＂ by introducing the simulated annealing algorithm. After judging the particle swarm optimization algorithm being trapped in local optimal solution, it could jump out and continue to search the global optimal solution. The re- suits show that the combination of algorithms on the convergence rate of the boom structure optimization is very sig- nificant, and it is of a high application value in engineering.
出处
《太原科技大学学报》
2013年第3期221-225,共5页
Journal of Taiyuan University of Science and Technology
关键词
臂架
参数化设计
结构优化
粒子群
模拟退火
crane jib, parametric design, structures optimal, particle swarm, simulated annealing
