基于神经网络与遗传算法的移动硬盘耐撞性能多目标优化设计

杨书仪; 刘德顺; 赵继云

基于神经网络与遗传算法的移动硬盘耐撞性能多目标优化设计

1.
湖南科技大学机电工程学院, 湘潭 411201;
2.
中国矿业大学, 徐州 221116

基金项目:

国家自然科学基金项目(51075139)

教育部科学技术研究重点项目(211120)

湖南省教育厅科学研究青年项目(10B030)

湖南省高校科技创新团队支持计划项目资助

详细信息

作者简介:
杨书仪(1972-)，副教授，博士，研究方向为冲击动力学和优化设计，ysy822@126.com，deshunliu@hotmail.com

计量
- 文章访问数: 141
- HTML全文浏览量: 30
- PDF下载量: 5
- 被引次数: 0
出版历程
- 收稿日期: 2011-04-29
- 刊出日期: 2015-06-10

Multi-objective Optimization for Mobile Hard Disk Crashworthiness Based on ANN and GA

1.
College of Electromechanical Engineering, Hunan University of Science and Technology, Xiangtan 411201;
2.
China University of Mining and Technology, Xuzhou 221116

摘要

摘要: 针对移动硬盘复杂的内部结构,遵循质量等效原则,建立有限元模型,结合均匀设计试验方法,进行移动硬盘跌落冲击有限元仿真。将试验数据作为训练样本,建立移动硬盘传动臂厚度、悬臂厚度及枢轴轴承刚度与磁盘接触面应力、磁头与磁盘间距之间的BP神经网络,运用遗传算法对移动硬盘结构参数进行多目标优化。研究表明:在考虑耐撞性能方面,运用该方法建立的设计变量与跌落冲击响应的非线性映射关系,对移动硬盘的关键零件参数设计具有理论指导意义。
- 移动硬盘 /
- 多目标优化 /
- 均匀设计 /
- 神经网络 /
- 遗传算法
Abstract: In view of inner structure and complying with quality equivalent principle, a 2.5 inch mobile hard disk was modeled based on ANSYS/LS-DYNA. The non-linear mapping relation between structural parameters of the key components and drop impact response was built using FEM (finite element method) and experimental design. Drop impact processes of different head actuator arm thickness, cantilever thickness and pivot bearing stiffness were simulated in order to obtain training specimen for the ANN (artificial neutral network). The BP ANN prediction model was established. Multiple objective optimization algorithms for crashworthiness of mobile hard disk were analyzed based on ANN and GA (genetic algorithm). The results indicate that the method is effective and may provide theory gist of preferences in key part parameter design.
- mobile hard disk /
- multi-objective optimization /
- uniform design /
- ANN /
- GA

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参考文献(9)

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