墨水池
喷嘴
计算机科学
人工神经网络
流量(数学)
人工智能
主成分分析
体积流量
过程(计算)
3D打印
计算机视觉
工程制图
生物医学工程
材料科学
机械工程
数学
工程类
机械
语音识别
复合材料
物理
几何学
操作系统
出处
期刊:Journal of Computational Methods in Sciences and Engineering
[IOS Press]
日期:2023-12-15
卷期号:23 (6): 3071-3080
摘要
Based on the development of the 3D vascular printer, the forming process of ink from the nozzle to the rotating rod was studied. In this study, to online detect the ink flow from the nozzle during 3D bioprinting of tubular tissue, we established a geometric model according to the region of interest (ROI) of the ink flow picture of 3D printing of tubular tissue, selected description features of the ink contour, and studied how to select mathematical expressions of the features. Principal component analysis (PCA) was used to simplify the image features into 15 features. We used a back propagation (BP) neural network to predict the printing ink flow. The results show that the error between the actual ink flow rate and the flow rate based on the BP neural network is within 5%. The BP neural network can be used to monitor the quality status of the printing target in real time, evaluate the 3D bioprinting quality online, and predict the printing ink flow for the subsequent improvement of the 3D bioprinting accuracy of tubular tissue.
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