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

Authors: Bin Yang; Hongwei Zhao; Yingfu Zhang

Addresses: School of Automobile and Transportation, Tianjin University of Technology and Education, Tianjin 300222, China; Great Wall Motor Company Limited, Hebei Baoding 071000, China ' College of Machinery and Engineering, Jilin University, Changchun 130025, China ' Great Wall Motor Company Limited, Hebei Baoding 071000, China

Abstract: 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.

Keywords: plasma spraying; nanostructured coatings; neural networks; PSO; particle swarm optimisation; process parameters; parameter optimisation; nanotechnology; ZrO2; zirconium dioxide; zirconia; Y2O3; yttrium oxide; yttria; spraying distance; spraying electric current; primary gas pressure; bonding strength.

DOI: 10.1504/IJMPT.2015.072236

International Journal of Materials and Product Technology, 2015 Vol.51 No.3, pp.220 - 227

Received: 07 Jul 2014
Accepted: 18 Oct 2014

Published online: 06 Oct 2015 *

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