摘要
The performance of an aerostatic bearing with a pocketed orifice-type restrictor is affected by the bearing size, pocket size, orifice design, supply pressure, and bearing load. This study proposes a modified particle swarm optimization (MPSO) algorithm to optimize a double-pad aerostatic bearing. In bearing optimization, the upper and lower bearing designs are independent and several design variables that affect bearing performance must be considered. This study also applies the concept of mutation from a genetic algorithm. The results show that the MPSO algorithm has a global search capability and high efficiency to optimize a problem with several design variables and that the mutation can provide an avenue for particles to escape from a local optimal value.
原文 | English |
---|---|
文章編號 | 021701 |
期刊 | Journal of Tribology |
卷 | 136 |
發行號 | 2 |
DOIs | |
出版狀態 | Published - 2014 1月 1 |
All Science Journal Classification (ASJC) codes
- 材料力學
- 機械工業
- 表面和介面
- 表面、塗料和薄膜