Research On The Spatter Behavior In Laser Powder Bed Fusion Process

The laser powder bed fusion technology breaks through the traditional mechanical processing technology process constraints with the basic molding principle of rapid prototyping and has outstanding advantages in terms of molding capability and cost.However,the quality of L-PBF molding is always the basic concern of researchers and users.As a high-energy beam processing technology,there is a violent and unavoidable spatter behavior during the forming process.Spatter behavior is not only the direct product of the interaction between laser and metal powder,but also often directly or indirectly affects the L-PBF process and the molding quality.Therefore,the study of spatter behavior is of far-reaching significance for understanding the mechanism of the interaction of laser with powder and the quality control mechanism of L-PBF molding.This article focuses on the following research on the spatter behavior during L-PBF molding:1.Based on the high-speed imaging technology,the information of two types of spatter behaviors of powder spatter and droplet spatter was obtained.And the types and formation and evolution mechanisms of PBF macro defects induced by the two spatter behaviors were qualitatively discussed and analyzed.In particular,the process of the collision of molten droplets with the powder bed was discussed,and the important role of the oxide film in the collision process was proposed.2.Based on the previous process research,combined with single track forming experiments and high-speed imaging technology,the article obtained image data of droplet spatter behavior in three typical processing states,and used digital image processing technology and statistical analysis technology to calculate the characteristics information of droplet spatter behavior images under each group,including droplet pixel size,droplet particle sputtering angle,droplet number,and droplet image shape information.Based on the above characteristics information,the statistical analysis technology was used to analyze the state of the micro-melt pool system under three typical processing states,which not only realizes the analysis of the interaction process of laser and powder with a low-cost detection method.3.Combining the morphology of single track and the droplet spatter behavior under different linear energy densities,the three typical processing states of PBF were distinguished and mapped.Using traditional machine learning Adaboost(CART)classification model and the Alex Net transfer learning to verify the rationality and accuracy of the droplet spatter behavior and the PBF processing state mapping model,respectively,and obtained 72.2% classification accuracy and 97.78% classification accuracy.It not only verifies the correlation between droplet spatter behavior and processing state,but also the reliability of the mapping model.At the same time,it reveals the value of further research on the characteristics of droplet spatter behavior in the future.4.Aiming at the filtering process of laser processing by-products such as spatters,fluid simulation technology was used to carry out research on the distribution and flow performance of the protective airflow field in the Dimetal-100 E molding cavity.According to the flow characteristics,the distribution area of the protective airflow field in the cavity is divided,and the interaction processes among each area were measured and discussed.In order to optimize the flow field distribution in the cavity,we tried to control the flow field distribution area by changing the size parameters of the molding cavity.And finally,under the increasing the height of the cavity,the height and fluidity of the effective protective gas atmosphere area were improved,which provides a clear optimization goal for the clear efficiency research of pollutants such as spatters in the future.