|Table of Contents|

High Speed Molten Pool Image Detection Based on Weighted Fusion and Parameter Extraction(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2023年02期
Page:
16-24
Research Field:
计算机科学与技术
Publishing date:

Info

Title:
High Speed Molten Pool Image Detection Based on Weighted Fusion and Parameter Extraction
Author(s):
Ling Xu1; 2; Xie Fei1; 2; 3; Yang Jiquan1; 2; Du Jun4; Miao Liguo3; 5; Suo Hongbo3
(1.School of Electrical and Automation Engineering,Nanjing Normal University,Nanjing 210023,China)
(2.Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing,Nanjing Normal University,Nanjing 210023,China)
(3.Nanjing Zhongke Raycham Laser Technology Co.,Ltd.,Nanjing 210023,China)
(4.The State Key Laboratory for Manufacturing Systems Engineering,Xi'an Jiaotong University,Xi'an 710049,China)
(5.School of Machanical Engineering,Shenyang University of Technology,Shenyang 110870,China)
Keywords:
molten pool detection; additive manufacturing; semantic segmentation; feature fusion; neural network
PACS:
TG441.7
DOI:
10.3969/j.issn.1672-1292.2023.02.003
Abstract:
In order to obtain the input parameters for feedback control of additive manufacturing using molten pool feature parameters,we propose a laser additive manufacturing molten pool semantic segmentation algorithm based on channel-weighted FPN,and a molten pool orientation,area and width feature parameter extraction algorithm based on image pixel threshold. The semantic segmentation algorithm mainly consists of a lightweight backbone neural network and a channel-weighted feature FPN network. The experimental results show that the segmentation speed of the molten pool image can reach 79.76 frames/s,and the mIoU and mAP can reach 90.53% and 95.79%,respectively,and the model size is only 90MB. Compared with other similar types of deep learning models,this algorithm improves the detection speed and reduces the model parameter size and size while ensuring accuracy. The molten pool image feature parameter extraction algorithm combines the pixel threshold distribution of the original image captured by the camera and the segmented image,and can accurately analyze and calculate the orientation,width and area feature parameters of the molten pool.

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Last Update: 2023-06-15