期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2019
卷号：252
期号：2
页码：1-8
DOI：10.1088/1755-1315/252/2/022092
出版社：IOP Publishing
摘要：Plasma spraying is a kind of thermal spraying technology widely used in parts production. However, the coating performance can't meet requirements due to process parameters and machining equipment, which caused a bad effect on overall product reliability. It is necessary to study the reliability of plasma spraying process. Firstly, seven controllable process parameters impacting on coating quality were determined, according to engineering experience. The uniform design was selected to find the most contributing factors and primary selection parameter combination was determined. For optimality design, the RBF neural network was trained and verified by sample data. The particle swarm optimization (PSO) algorithm was used to optimize the RBF model. The optimal process parameters were obtained by improved PSO. The optimization of the process improves the process reliability of the plasma spraying and plays an important role in ensuring the reliability of the part.
