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选区激光熔化孔洞试样内表面粗糙度分析与预测

Analysis and Prediction of Internal Surface Roughness of Selected Area Laser Melted Hole Specimens

  • 摘要: 本研究旨在探讨试样结构对选区激光熔化工艺表面粗糙度的影响,并建立理论模型以预测其表面粗糙度。以内孔的角度和半径与粗糙度的关系为参数构建数学模型,分析不同参数下成形零件的表面形貌,探究不同参数对表面粗糙度的影响。分析影响试样表面粗糙度的关键因素,包括阶梯效应、粉末吸附和翘曲变形等因素都会影响表面粗糙度。建立成型结构与表面粗糙度的预测模型。实验结果显示,不同的角度和孔径都会显著影响试样表面粗糙度。当孔径打印角度超过50°时,孔径内表面的粗糙度值开始急剧增大,例如4 mm孔50°情况下,其粗糙度为7.01 μm,在70°情况下则达到24.53 μm。且随着角度和孔径的增大,各因素会共同影响试样表面质量。通过数学模型的构建发现,粗糙度预测在中低角度时预测效果良好,当打印角度增至80°时会出现明显误差。通过模型可以用参数对表面粗糙度进行适当准确预测,为优化表面提供有力的理论依据和技术支持。

     

    Abstract: This study aims to investigate the impact of sample structure on surface roughness in Selective Laser Melting (SLM) processes and to establish a theoretical model for predicting surface roughness. A mathematical model is constructed based on the relationship between the angle and radius of internal holes and their roughness, analyzing the surface morphology of formed parts under different parameters and exploring the influence of various parameters on surface roughness. Key factors affecting the surface roughness of samples are analyzed, including the stair-stepping effect, powder adhesion, and warpage deformation, all of which can influence surface roughness. A predictive model linking the formed structure with surface roughness is established. Experimental results show that different angles and hole diameters significantly affect the surface roughness of samples. When the printing angle of the hole exceeds 50°, the roughness value of the inner surface of the hole begins to increase sharply. For instance, at a 4 mm hole diameter and a 50° angle, the roughness is 7.01 μm; this increases to 24.53 μm at a 70° angle. As the angle and hole diameter increase, these factors collectively impact the surface quality of the samples. Through the construction of the mathematical model, it was found that roughness prediction is effective at medium to low angles, but noticeable errors occur when the printing angle increases to 80°. The model allows for appropriately accurate predictions of surface roughness using parameters, providing a solid theoretical basis and technical support for optimizing surface quality.

     

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