Process Parameters Optimization of Plasma Spraying Nanostructured Coating Based on Particle Swarm Optimization Algorithm

被引：0
作者：
Yang, Bin [1 ]
机构：
[1] Tianjin Univ Technol & Educ, Sch Automobile & Transportat, Tianjin 300222, Peoples R China
来源：
MATERIALS SCIENCE AND PROCESSING, ENVIRONMENTAL ENGINEERING AND INFORMATION TECHNOLOGIES | 2014年 / 665卷
关键词：
Plasma Spraying; Nanostructured Coating; BP Neural Network; Particle Swarm Optimization Algorithm; Process Parameters Optimization;
D O I：
10.4028/www.scientific.net/AMM.665.68
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
Process parameters of plasma spraying nanostructured Al2O3-13% TiO2 (mass fraction) coating were optimized based on particle swarm optimization (PSO) algorithm. BP neural network was applied to compute fitness of PSO algorithm. A BP neural network model was built. Process parameters of coating were optimized based on PSO algorithm. The results shown that maximal bonding strength was 33.08MPa. Process parameters of plasma spraying nanostructured Al2O3-13% TiO2 (mass fraction) coating were obtained. The results were superior to design of orthogonal optimization. It provided definite reference for selecting the best process parameters of plasma spraying nanostructured Al2O3-13% TiO2 (mass fraction) coating.
引用
收藏
页码：68 / 71
页数：4
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