Laser & Optoelectronics Progress, Volume. 59, Issue 19, 1916004(2022)

Investigation of Spatter Characteristics in Selective Laser Melting Based on Maximum Entropy Threshold Segmentation Algorithm

Linjun Zhao1, Guoqing Zhang2,3、*, Dalin Zhang1, and Zhiwen Li4
Author Affiliations
  • 1College of Engineering and Technology, Nanchang Vocational University, Nanchang 330500, Jiangxi, China
  • 2Institute of Technological Sciences, Wuhan University, Wuhan 430072, Hubei, China
  • 3Shenzhen Research Institute, Wuhan University, Shenzhen 518057, Guangdong, China
  • 4School of Mechanical Engineering, Jiangxi Technical College of Manufacturing, Nanchang 330095, Jiangxi, China
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    The spatter morphology during selective laser melting (SLM) processing varies with process parameters, and it is difficult to achieve spatter extraction under all process parameters. The spatter extraction method based on traditional threshold segmentation only supports some process parameters and has no error analysis work, and the processing results cannot reflect the real spatter state. This paper proposes a robust image processing method to extract and process them based on the spatter images of the SLM process collected by high-speed cameras.The image processing method includes five steps, in which the threshold segmentation process depends on maximum entropy threshold segmentation algorithm. The results show that the spatter image processing method can accurately extract the spatter information under multiple process parameters. When the laser power is in the range from 100 W to 150 W, the change in the spatter area and number is determined by the molten state of the powder. And the reduction of spatter area and number is caused by spatter superposition when the laser power is in the range from 150 W to 200 W.

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    Linjun Zhao, Guoqing Zhang, Dalin Zhang, Zhiwen Li. Investigation of Spatter Characteristics in Selective Laser Melting Based on Maximum Entropy Threshold Segmentation Algorithm[J]. Laser & Optoelectronics Progress, 2022, 59(19): 1916004

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    Paper Information

    Category: Materials

    Received: Sep. 13, 2021

    Accepted: Oct. 8, 2021

    Published Online: Sep. 23, 2022

    The Author Email: Zhang Guoqing (guoqingzhang_1989@126.com)

    DOI:10.3788/LOP202259.1916004

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