In-Situ Monitoring and Diagnosing for Fused Filament Fabrication Process Based on Vibration Sensors

Sensors - Tập 19 Số 11 - Trang 2589
Yongxiang Li1,2, Wei Zhao1, Qiushi Li1,2, Tongcai Wang1, Gong Wang1,2
1CAS Key Laboratory of Space Manufacturing Technology, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China
2University of Chinese Academy of Science, Beijing, 100049, China

Tóm tắt

Fused filament fabrication (FFF) is one of the most widely used additive manufacturing (AM) technologies and it has great potential in fabricating prototypes with complex geometry. For high quality manufacturing, monitoring the products in real time is as important as maintaining the FFF machine in the normal state. This paper introduces an approach that is based on the vibration sensors and data-driven methods for in-situ monitoring and diagnosing the FFF process. The least squares support vector machine (LS-SVM) algorithm has been applied for identifying the normal and filament jam states of the FFF machine, besides fault diagnosis in real time. The identification accuracy for the case studies explored here using LS-SVM is greater than 90%. Furthermore, to ensure the product quality during the FFF process, the back-propagation neural network (BPNN) algorithm has been used to monitor and diagnose the quality defects, as well as the warpage and material stack caused by abnormal leakage for the products in-situ. The diagnosis accuracy for the case studies explored here using BPNN is greater than 95%. Results from the experiments show that the proposed approach can accurately recognize the machine failures and quality defects during the FFF process, thus effectively assuring the product quality.

Từ khóa


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Sensors

Tập 19 Số 11

2589

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