{"title":"基于Kriging模型的汽车覆盖件成形回弹优化设计","authors":"Jinjin Zhai, Qing Zhang, Zengzeng Zhang, Yuantao Sun, X. Qin, Xuehua Chen","doi":"10.1109/ICACMVE.2019.00013","DOIUrl":null,"url":null,"abstract":"The sheet metal forming method is often used in automotive panels, which will face springback defects that seriously affects the quality of parts. Therefore, it is necessary to evaluate the impact of springback defects in early design stage in order to optimize the design scheme. Aiming at this problem, firstly the finite element model of automobile panel is established and its forming process is simulated. Then sensitivity analysis method is used to select the factors that have great influence on the forming quality of automobile panel, and Box-Behnken design method is used to gain locally distributed test sample points. Afterwards an approximate model based on Kriging model theory is established. The response is predicted for the finite element method. Finally, the minimization of springback is taken as the optimal objective, combined with Kriging approximation model, and the genetic algorithm is used to optimize the design scheme with the help of MBC (Model-Based Calibration) toolbox of MATLAB software. The optimization result proves the effectiveness of the proposed method. The springback of the optimal design is 74.43% less than that of the initial design, and the forming quality is improved significantly.","PeriodicalId":375616,"journal":{"name":"2019 International Conference on Advances in Construction Machinery and Vehicle Engineering (ICACMVE)","volume":"188 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Design for Springback of Automotive Panel Forming with Kriging Model\",\"authors\":\"Jinjin Zhai, Qing Zhang, Zengzeng Zhang, Yuantao Sun, X. Qin, Xuehua Chen\",\"doi\":\"10.1109/ICACMVE.2019.00013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The sheet metal forming method is often used in automotive panels, which will face springback defects that seriously affects the quality of parts. Therefore, it is necessary to evaluate the impact of springback defects in early design stage in order to optimize the design scheme. Aiming at this problem, firstly the finite element model of automobile panel is established and its forming process is simulated. Then sensitivity analysis method is used to select the factors that have great influence on the forming quality of automobile panel, and Box-Behnken design method is used to gain locally distributed test sample points. Afterwards an approximate model based on Kriging model theory is established. The response is predicted for the finite element method. Finally, the minimization of springback is taken as the optimal objective, combined with Kriging approximation model, and the genetic algorithm is used to optimize the design scheme with the help of MBC (Model-Based Calibration) toolbox of MATLAB software. The optimization result proves the effectiveness of the proposed method. The springback of the optimal design is 74.43% less than that of the initial design, and the forming quality is improved significantly.\",\"PeriodicalId\":375616,\"journal\":{\"name\":\"2019 International Conference on Advances in Construction Machinery and Vehicle Engineering (ICACMVE)\",\"volume\":\"188 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Advances in Construction Machinery and Vehicle Engineering (ICACMVE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACMVE.2019.00013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Advances in Construction Machinery and Vehicle Engineering (ICACMVE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACMVE.2019.00013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
汽车覆盖件常采用钣金成形方法,会面临回弹缺陷,严重影响零件质量。因此,有必要在设计初期对回弹缺陷的影响进行评估,以优化设计方案。针对这一问题,首先建立了汽车覆盖件的有限元模型,并对其成形过程进行了仿真。然后采用灵敏度分析法选取对汽车覆盖件成形质量影响较大的因素,采用Box-Behnken设计方法获得局部分布的试验样点;然后建立了基于克里格模型理论的近似模型。用有限元法对响应进行了预测。最后,以回弹最小为优化目标,结合Kriging近似模型,借助MATLAB软件的MBC (model - based Calibration)工具箱,采用遗传算法对设计方案进行优化。优化结果证明了所提方法的有效性。优化后的回弹量比初始设计减少了74.43%,成形质量明显提高。
Optimal Design for Springback of Automotive Panel Forming with Kriging Model
The sheet metal forming method is often used in automotive panels, which will face springback defects that seriously affects the quality of parts. Therefore, it is necessary to evaluate the impact of springback defects in early design stage in order to optimize the design scheme. Aiming at this problem, firstly the finite element model of automobile panel is established and its forming process is simulated. Then sensitivity analysis method is used to select the factors that have great influence on the forming quality of automobile panel, and Box-Behnken design method is used to gain locally distributed test sample points. Afterwards an approximate model based on Kriging model theory is established. The response is predicted for the finite element method. Finally, the minimization of springback is taken as the optimal objective, combined with Kriging approximation model, and the genetic algorithm is used to optimize the design scheme with the help of MBC (Model-Based Calibration) toolbox of MATLAB software. The optimization result proves the effectiveness of the proposed method. The springback of the optimal design is 74.43% less than that of the initial design, and the forming quality is improved significantly.