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.
A Modified Particle Swarm Optimization Algorithm for the Design of a Double-Pad Aerostatic Bearing With a Pocketed Orifice-Type Restrictor
Contributed by the Tribology Division of ASME for publication in the JOURNAL OF TRIBOLOGY. Manuscript received May 23, 2013; final manuscript received November 10, 2013; published online December 27, 2013. Assoc. Editor: Prof. C. Fred Higgs III.
Chang, S. H., and Jeng, Y. R. (December 27, 2013). "A Modified Particle Swarm Optimization Algorithm for the Design of a Double-Pad Aerostatic Bearing With a Pocketed Orifice-Type Restrictor." ASME. J. Tribol. April 2014; 136(2): 021701. https://doi.org/10.1115/1.4026061
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