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华南理工大学机械与汽车工程学院, 广东 广州 510640
收稿日期:2016-04-20,
修回日期:2016-05-17,
纸质出版日期:2016-11-14
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白玉超, 杨永强, 王迪等. 激光选区熔化直接成型高致密锡青铜零件[J]. 光学精密工程, 2016,24(10s): 484-492
BAI Yu-chao, YANG Yong-qiang, WANG Di etc. High relative density tin bronze parts directly manufactured by selective laser melting[J]. Editorial Office of Optics and Precision Engineering, 2016,24(10s): 484-492
白玉超, 杨永强, 王迪等. 激光选区熔化直接成型高致密锡青铜零件[J]. 光学精密工程, 2016,24(10s): 484-492 DOI: 10.3788/OPE.20162413.0484.
BAI Yu-chao, YANG Yong-qiang, WANG Di etc. High relative density tin bronze parts directly manufactured by selective laser melting[J]. Editorial Office of Optics and Precision Engineering, 2016,24(10s): 484-492 DOI: 10.3788/OPE.20162413.0484.
为了获取高致密度激光选区熔化锡青铜成型件,直接制造出具有典型曲面、薄壁、圆孔特征的锡青铜功能零件,对激光功率、扫描速度和扫描间距三个关键因素对致密度的影响进行研究。以激光选区熔化成型锡青铜成型件为研究对象,以成型件致密度为评价指标,设计三因素四水平正交实验。根据正交实验结果,通过BP神经网络和遗传算法对成型工艺参数进行优化。采用MicroCT技术和阿基米德排水法研究优化后的成型件致密性,并通过超景深立体成像技术研究其表面形貌,最后采用优化工艺参数成型具有典型结构特征的风轮模型。实验结果表明:激光功率、扫描间距、扫描速度对致密度均具有重要的影响,影响程度依次减弱;最优工艺参数为:激光功率177W,扫描速度327mm/s,扫描间距0.082mm,该工艺下样品实际测量致密度99.07%与预测值99.12%基本符合;MicroCT图像显示优化后样品内部致密性良好,无明显夹杂、间隙等缺陷;可直接成型出具有曲面、薄壁、圆孔典型特征的风轮模型,表面无球化、裂纹、悬垂物等缺陷。以正交实验为基础,采用BP神经网络与遗传算法对成型工艺参数优化是可行的,成型致密度满足要求。
In order to obtain high density tin bronze parts and functional components with typical curved
thin-walled
round features manufactured by Selective Laser Melting
the influence of three key factors of laser power
scanning speed and scanning distance on the density of tin bronze parts manufactured by selective was researched. Design a three factors and four levels orthogonal experiment. And according to the results of experiment
the process parameters of parts are optimized by the method of BP neural network and genetic algorithm. The density of optimized parts has been researched by MicroCT and Archimedes drainage
and the surface topography of optimized parts has been studied by the technology of digital stereo imaging. Then a wind turbine model with typical structure characteristics has been manufactured by the optimized process parameters. The experimental results show that the laser power
scanning distance and scanning speed have important influence on the density of the laser
and the degree of the influence is weakened in turn. Optimum parameter is laser power of 177W
scanning speed of 327mm/s and scanning pitch of 0.082mm. under the process
the density that measured by experiment is 99.7%
which is nearly the same as the theoretical optimization results of 99.12%. So the error of the two results is very small. The MicroCT image shows that there is no obvious inclusions
gap and other defects inside the parts. The wind turbines model with the typical characteristics of curved surface
thin wall and round hole can be directly manufactured
and the surface of the part have no ball
crack
and other defects. Therefore
the method for optimizing molding process parameters
which is based on the orthogonal experiment and combined with BP neural network and genetic algorithm
is feasible. The relative density of parts meets the requirement.
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