English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The performance of magnetic bearing is determined by its electromagnetic parameters and mechanical parameters. In order to improve the performance of hybrid magnetic bearing (HMB) to better meet the engineering requirements, which needs to be optimized, a multi-objective optimization method based on genetic particle swarm optimization algorithm (GAPSO) is proposed in this paper to solve the problem that the optimization objectives are not coordinated during the optimization design. By introducing the working principle of HMB, a mathematical model of suspension force is established, and its rationality is verified by the finite-element method. By optimization, the suspension force of the HMB is increased by 18.5%, and the volume is reduced by 22%. The optimization results show that the multi-objective optimization algorithm based on GAPSO can effectively improve the performance of HMB.

MULTI-OBJECTIVE OPTIMIZATION DESIGN OF MAGNETIC BEARING BASED ON GENETIC PARTICLE SWARM OPTIMIZATION