Optimization of passive control performance for different hard disk drives subjected to shock excitation

作     者：Seyed Rashid Alavi Mehdi Rahmati Saeed Ziaei-Rad 

作者机构：Department of Mechanical Engineering Isfahan University of Technology Isfahan 84156-83111 Iran Isfahan Mathematics House Isfahan 81698-51177 Iran 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2017年第24卷第4期

页      面：891-899页

核心收录：

学科分类：12[管理学] 08[工学] 0810[工学-信息与通信工程] 083002[工学-环境工程] 1204[管理学-公共管理] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 120402[管理学-社会医学与卫生事业管理(可授管理学、医学学位)] 0806[工学-冶金工程] 0837[工学-安全科学与工程] 0805[工学-材料科学与工程（可授工学、理学学位）] 0703[理学-化学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：hard disk drive passive control shock excitation sequential quadratic programming genetic algorithm rubber 

摘      要：Laptop personal computers(LPCs) and their components are vulnerable devices in harsh mechanical environments. One of the most sensitive components of LPCs is hard disk drive(HDD) which needs to be protected against damages attributable to shock and vibration in order to have better magnetic read/write performance. In the present work, a LPC and its HDD are modeled as two degrees of freedom system and the nonlinear optimization method is employed to perform a passive control through minimizing peak of HDD absolute acceleration caused by a base shock excitation. The presented shock excitation is considered as half-sine pulse of acceleration. In addition, eleven inequality constraints are defined based on geometrical limitations and allowable intervals of lumped modal parameters. The target of the optimization is to reach optimum modal parameters of rubber mounts and rubber feet as design variables and subsequently propose new characteristics of rubber mounts and rubber feet to be manufactured for the HDD protection against shock excitation. The genetic algorithm and the modified constrained steepest descent algorithm are employed in order to solve the nonlinear optimization problem for three widely-used commercial cases of HDD. Finally, the results of both optimization methods are compared to make sure about their accuracy.