摘要
针对激光熔覆过程中两种粉末混合喷射后实际成分与设计成分偏差的问题,设计了钛(Ti)/羟基磷灰石(HA)粉末收集实验,该实验将未分离粉末宽度作为成分评价标准;然后基于响应曲面法建立了未分离粉末宽度与激光工艺参数之间的数学模型;通过对回归模型求极值,确定合理的工艺参数,抑制了激光沉积过程中粉末成分偏差现象。实验结果表明:离焦量对Ti/HA粉末分离的影响最大,其次是扫描速度,送粉率对预混合粉末分离的影响最小;未分离粉末宽度随着离焦量的增大而呈现先增大后减小的趋势,并随着扫描速度的增大而减小;当离焦量为-3^-1.5 mm,扫描速度为0~4 mm·s-1时,未分离粉末宽度较大,该范围内的工艺参数有利于改善Ti/HA生物医学材料成分配比不准确的问题。
In this paper, the titanium(Ti)/hydroxyapatite(HA) powders collection experiment was designed using the unseparated powders width value as the component evaluation standard to overcome the problem of deviation between the actual composition and the designed composition after the two powders are mixed and sprayed in the laser cladding process. Based on the response surface method, the mathematical model between the width of the unseparated powders and process parameters of the laser was established. Through the calculation of the extreme value of the regression model and determination of the reasonable process parameters, the powders composition deviation in the laser deposition process was inhibited. The experimental results reveal that defocusing distance has the most significant influence on the Ti/HA powder separation, followed by the scanning speed and powder feeding rate. The unseparated powders width initially increases and then decreases with the increase of defocusing distance;meanwhile, it decreases with the increase of the scanning speed. Moreover, when the defocusing distance is-3 mm to-1.5 mm and the scanning speed is 0 to 4 mm·s-1, the width value of the unseparated powders is large, and the process parameters in this range help to improve the inaccurate composition raio of Ti/HA biomedical materilas.
作者
王呈栋
鲍振林
马健溥
张克栋
Wang Chengdong;Bao Zhenlin;Ma Jianpu;Zhang Kedong(School of Mechanical and Electric Engineering Soochow University Suzhou,Jiangsu 215021,China)
出处
《中国激光》
EI
CAS
CSCD
北大核心
2020年第12期57-68,共12页
Chinese Journal of Lasers
基金
国家自然科学基金(51805344,51905360)
中国博士后科学基金面上资助项目(2020M671576)。
关键词
材料
Ti/HA材料
激光熔覆
粉末分离
工艺参数优化
materials
Ti/HA materials
laser cladding
powder separation
process parameter optimization