抛光
材料科学
表面粗糙度
钛镍合金
响应面法
表面光洁度
选择性激光熔化
合金
形状记忆合金
冶金
复合材料
计算机科学
机器学习
微观结构
作者
Jianwei Che,Guangfeng Shi,Ying Xu,Lunxiang Li,Jingran Zhang,Tianwen Zhou
摘要
NiTi alloy has unique super elasticity and shape memory, and is widely used in aerospace, biomedical and intelligent control fields. At present, the mainstream selective laser melting technology (SLM) can prepare NiTi alloy with complex structure, but the surface roughness is poor, which needs to be processed by electrochemical polishing. In order to optimize the electrochemical polishing process parameters, Box-Behnken response surface was used for regression analysis in this paper. Surface roughness was used as an evaluation index to analyze the influence of voltage, temperature, and reaction time on roughness. Based on the results of electrochemical polishing experiments, a prediction model for surface roughness was established and its response surface graph was obtained, the significance of the prediction model and parameters was tested using analysis of variance. The results indicate that the model can effectively predict the surface roughness of SLM-NiTi alloy after electrochemical polishing, and the best parameters are as follows: the voltage is 13.5V, the temperature is 27.7 C , and the reaction time is 53 seconds, which lays the foundation for high efficiency and high quality polishing of SLM-NiTi alloy, and has important scientific significance and research value for expanding the application of SLM-NiTi alloy parts.
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