面向等离子喷涂涂层质量调控的工艺优化方法研究现状

doi:10.11896/cldb.20080144

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Abstract Plasma spraying, as an important surface engineering technology, has been widely used to improve the wear resistance, corrosion resis-tance and high temperature resistance of parts. Due to the fact that the properties of plasma sprayed coating is determined by many factors, it is of great significance to investigate the complex but related mapping relationship between coating quality and process parameters for obtaining high quality coating and improving spraying efficiency. In this paper, the research status of orthogonal experiment, response method, artificial neural network and other mathematical statistical methods in the field of coating quality optimization is reviewed, and the characteristics of various statistical methods and the variation law of typical coating with process parameters are summarized. The results indicate that the micro-hardness and bonding strength of typical coatings are improved significantly after optimization, i.e. Al₂O₃ coating and Ni coating, etc; the addition of TiO₂ has a significant effect on the properties of the Al₂O₃ coating; different classification methods of response surface are introduced in detail. Based on the analysis of typical coating experiments, it is concluded that BBD design is more widely used when the number of factors is the same and there is no danger that the experimental points exceed the original level; the research of traditional and improved artificial neural network mo-dels in prediction and optimization of plasma sprayed coatings are introduced. Finally, the application of mathematical statistics method in the field of plasma spraying coating quality optimization is summarized, and the future development direction is prospected.

Key words： plasma spraying parameter optimization properties of coating mathematical statistics method

Published: 30 November 2021

CLC number:

TG17

Fund:Natural Science Foundation of Jiangsu Province (BK20191036) and Foundation of Research Project of China (61400040407).

About author:: Bingyuan Han is an associate professor and postgra-duate tutor of Automobile and Traffic Engineering College of Jiangsu University of Technology. She graduated from Vehicle application engineering of Northeast Fo-restry University in 2013 and had a Ph.D degree in engineering.In recent 5 years, she has presided over and participated in more than 10 scientific research projects, including the 13th five year plan pre-research fund, Jiangsu Natural Science Foundation, Jiangsu University Natural Science Research Project, Jiangsu Engineering Technology Research Center Construction Project, Jiangsu Industry University Research Institute Joint Innovation Fund Forward Looking Joint Research Project, Changzhou Public Technology Service Platform Project, and published more than 20 related papers, of which 5 were included in SCI more than 10 articles were included in EI; 5 teaching materials were edited by deputy editor and participated in editing, guiding students to complete 2 practical and innovative training programs for college students.Her research interests are Green disassembly and parts remanufacturing of end of life vehicles.

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	HAN Bingyuan
	XU Wenwen
	ZHU Sheng
	HUANG Qingwei
	LEI Weining
	HANG Weixing
	DU Wei

Cite this article:

HAN Bingyuan,XU Wenwen,ZHU Sheng, et al. Research on Multi-factor Parameter Optimization Methods for Quality Control of Plasma Spraying Coatings:a Review[J]. Materials Reports, 2021, 35(21): 21105-21112.

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http://www.mater-rep.com/EN/10.11896/cldb.20080144 OR http://www.mater-rep.com/EN/Y2021/V35/I21/21105

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