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| Study on Factors Affecting Springback and Application of Data Mining in Springback Analysis | |
| 作者姓名： | 张少睿 罗超 彭颖红 李大永 杨洪波 |
| 作者单位： | [1]SchoolofMechanicEng.,ShanghaiJiaotongUniv.,Shanghai200030,China [2]SchoolofMaterialsScienceandEng.,CentralSouthUniv.,Changsha410083 [3]Dept.ofPlasticityTechnology,ShanghaiJiaotongUniv.,Shanghai200030 |
| 基金项目： | the Shanghai Post-Phosphor Plan ( No.0 1QMH14 11) |
| 摘 要： | Springback of sheet metal induced by elastic recovery is one of major defects in sheet metal forming processed. Springback is influenced by many factors including properties of the sheet material and processing conditions. In this paper, a springback simulation was conducted and comparisons between the results based on different processing variables were illustrated. The discovery of knowledge of the effects of geometry and process parameters on springback from FEM results becomes increasingly important, as the number of numerical simulation has grown exponentially. Data mining is an effective tool to realize knowledge discovery in simulation results. A datamining algorithm, rough sets theory (RST), was applied to analyze the effects of process parameters on springback in U-bending. |
| 关 键 词： | 数据挖掘 弹性恢复 金属薄片 成型加工 仿真 FEM 粗糙集理论 |
Study on Factors Affecting Springback and Application of Data Mining in Springback Analysis |
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| ZHANG Shao-rui ,LUO Chao ,PENG Ying-hong LI Da-yong ,YANG Hong-bo.Study on Factors Affecting Springback and Application of Data Mining in Springback Analysis[J].Journal of Shanghai Jiaotong university,2003,8(2):192-196. | |
| Authors: | ZHANG Shao-rui LUO Chao PENG Ying-hong LI Da-yong YANG Hong-bo |
| Institution: | 1. School of Mechanic Eng. , Shanghai Jiaotong Univ. , Shanghai 200030, China 2. School of Materials Science and Eng. , Central South Univ. , Changsha 410083 3. Dept. of Plasticity Technology, Shanghai Jiaotong Univ. , Shanghai 200030 |
| Abstract: | Springback of sheet metal induced by elastic recovery is one of major defects in sheet metal forming processed. Springback is influenced by many factors including properties of the sheet material and processing conditions. In this paper, a springback simulation was conducted and comparisons between the results based on different processing variables were illustrated. The discovery of knowledge of the effects of geometry and process parameters on springback from FEM results becomes increasingly important, as the number of numerical simulation has grown exponentially. Data mining is an effective tool to realize knowledge discovery in simulation results. A data-mining algorithm, rough sets theory (RST), was applied to analyze the effects of process parameters on springback in U-bending. |
| Keywords: | FEM springback data mining rough sets theory principal component analysis |
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