A new approach to simulate coating thickness in cold spray

SURFACE & COATINGS TECHNOLOGY

卷:382

Article

Wu, Hongjian¹  Xie, Xinliang¹  Liu, Meimei¹  Chen, Chaoyue²  Liao, Hanlin¹  Zhang, Yicha³  Deng, Sihao¹ 

[1] Univ Bourgogne Franche Comte, UTBM, CNRS, ICB,PMDM,LERMPS,UMR 6303, F-90010 Belfort, France

[2] Shanghai Univ, Sch Mat Sci & Engn, State Key Lab Adv Special Steels, Shanghai 200444, Peoples R China

[3] Univ Bourgogne Franche Comte, UTBM, CNRS, ICB,COMM,UMR 6303, F-90010 Belfort, France

关键词: Coating thickness model;    Simulation;    Shadow effects;    Relative deposition efficiency;    Cold spray;    Robot;   

DOI  :  10.1016/j.surfcoat.2019.125151

来源: Elsevier

【 摘 要 】

In the process of cold spray on complex components, the coating thickness is an important indicator to monitor and control. Current methods such as destructive tests or direct mechanical measurements can only be performed after spraying. Besides, these methods lead to production shutdown and additional costs. This article presents a novel approach predicting coating thickness for components with complex curved surfaces, especially in the case of shadow effects. Firstly, a three-dimensional geometric model of the coating profile based on Gaussian distribution was developed. In addition, the relative deposition efficiency (RDE) resulting from the different robot kinematic parameters was illustrated in detail. Secondly, this model was coupled with robotic trajectories and processing parameters to simulate coating deposition in robotic off-line programming software. Finally, the coating morphologies as well as the predicted coating thickness were presented in a graphical virtual environment. According to the results of the simulation, the robot trajectory, operating parameters and spray strategy can be adjusted with iteration in the feedback loop to achieve the desired coating thickness distribution. Both numerical and experimental verifications were carried out in the end of this study. The results show that this proposed method has a reliable prediction accuracy for practice.

【 授权许可】

Free