Analysis and optimization of variable depth increments in sheet metal incremental forming
来源期刊:中南大学学报(英文版)2014年第7期
论文作者:LI Jun-chao(李军超) WANG Bin(王宾) ZHOU Tong-gui(周同贵)
文章页码:2553 - 2559
Key words:incremental forming; numerical simulation; variable depth increment; genetic algorithm; optimization
Abstract: A method utilizing variable depth increments during incremental forming was proposed and then optimized based on numerical simulation and intelligent algorithm. Initially, a finite element method (FEM) model was set up and then experimentally verified. And the relation between depth increment and the minimum thickness tmin as well as its location was analyzed through the FEM model. Afterwards, the variation of depth increments was defined. The designed part was divided into three areas according to the main deformation mechanism, with Di (i=1, 2) representing the two dividing locations. And three different values of depth increment, Δzi (i=1, 2, 3) were utilized for the three areas, respectively. Additionally, an orthogonal test was established to research the relation between the five process parameters (D and Δz) and tmin as well as its location. The result shows that Δz2 has the most significant influence on the thickness distribution for the corresponding area is the largest one. Finally, a single evaluating indicator, taking into account of both tmin and its location, was formatted with a linear weighted model. And the process parameters were optimized through a genetic algorithm integrated with an artificial neural network based on the evaluating index. The result shows that the proposed algorithm is satisfactory for the optimization of variable depth increment.
LI Jun-chao(李军超), WANG Bin(王宾), ZHOU Tong-gui(周同贵)
(College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China)
Abstract:A method utilizing variable depth increments during incremental forming was proposed and then optimized based on numerical simulation and intelligent algorithm. Initially, a finite element method (FEM) model was set up and then experimentally verified. And the relation between depth increment and the minimum thickness tmin as well as its location was analyzed through the FEM model. Afterwards, the variation of depth increments was defined. The designed part was divided into three areas according to the main deformation mechanism, with Di (i=1, 2) representing the two dividing locations. And three different values of depth increment, Δzi (i=1, 2, 3) were utilized for the three areas, respectively. Additionally, an orthogonal test was established to research the relation between the five process parameters (D and Δz) and tmin as well as its location. The result shows that Δz2 has the most significant influence on the thickness distribution for the corresponding area is the largest one. Finally, a single evaluating indicator, taking into account of both tmin and its location, was formatted with a linear weighted model. And the process parameters were optimized through a genetic algorithm integrated with an artificial neural network based on the evaluating index. The result shows that the proposed algorithm is satisfactory for the optimization of variable depth increment.
Key words:incremental forming; numerical simulation; variable depth increment; genetic algorithm; optimization