Process parameter optimisation for plasma sprayed nanostructured ZrO2-7%Y2O3 coatings based on PSO algorithm

作者：Yang, Bin^*; Zhao, Hongwei; Zhang, Yingfu

来源：International Journal of Materials and Product Technology, 2015, 51(3): 220-227.

DOI：10.1504/IJMPT.2015.072236

• plasma spraying
• nanostructured coating
• neural networks
• PSO algorithms
• process parameters optimisation

The process parameters of plasma sprayed nanostructured ZrO2-7%Y2O3 coatings were optimised based on a particle swarm optimisation (PSO) algorithm. A BP neural network was applied to compute the fit of the PSO algorithm, and was assembled with four process parameters which included spraying distance, spraying electric current, primary gas pressure, and secondary gas pressure as the inputs; the bonding strength of the coating was the output. The results of the PSO algorithm and BP neural network show that the maximal bonding strength of the coatings was 42.5822 MPa. And the optimal process parameters discovered in this research for the plasma sprayed nanostructured ZrO2-7%Y2O3 coatings are a spraying distance of 80 mm, spraying electric current of 994.3707 A, primary gas pressure of 0.2575 MPa, and secondary gas pressure 1.1611 MPa.

• 出版日期2015
• 单位吉林大学; 天津职业技术师范大学