Development of a New Model for the Fixture Design and Clamping Optimization
E. H. Cao; J.H. Su; Z.Y Liu; H. Qiao; Su JH(苏建华)
2014
Conference NameWorld Congress on Intelligent Control and Automation
Source PublicationWorld Congress on Intelligent Control and Automation
Conference Date2014年6月27日-6月30日
Conference Place沈阳
AbstractWorkpiece deformation must be controlled in the manufacturing process and other engineering application. Fixture configuration (position), clamping force and temperature are main aspects that influence the degree and distribution of Workpiece deformation. This paper takes large optical glass as an example, develop a new multiple kernel learning method to discuss the optimal fixture design. The proposed method uses two layers regressions to group and order the data sources by the weights of the kernels and the factors of the layers. Since that, the influences of the clamps and the temperature can be evaluated by grouping them into different layers. Then, based on the proposed model, the optimal magnitude and positions of clamping forces can be obtained. The experiments show is effective for the optical element clamping optimization analysis.
KeywordFixture Design
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12459
Collection复杂系统管理与控制国家重点实验室_机器人理论与应用
Corresponding AuthorSu JH(苏建华)
AffiliationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
E. H. Cao,J.H. Su,Z.Y Liu,et al. Development of a New Model for the Fixture Design and Clamping Optimization[C],2014.
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