Abstract
During the procedure of 3D printing in Fused Deposition Molding (FDM), building faults, such as Congealed-Material (CM), empty printing, substrate deformation, warped edges and fused wire drawing, often occur. However, most FDM machines lack online monitor systems which lead to huge waste of materials and time. This paper combines an acceleration sensor with vision sensors to monitor CM faults during 3D printing in FDM. An acceleration sensor is used to collect signals during a printing procedure and then abnormal signals are found when nozzle collides with CM. Subsequently, CM can be detected through the STFT algorithm. Furthermore, acceleration data can provide fault characteristics for on-line monitoring. Finally, a camera is used to obtain 3D print model pictures and then an image processing algorithm is studied. An image window is used to reduce calculation amount and extract useful model features. Then, a connected region area is calculated and the largest area region is selected after a threshold and a region are connected. Through image processing, online CM detection can be realized, which provides a foundation for further positioning and removal of CM.
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Acknowledgement
This work is partially supported by Guangdong Ordinary Universities Youth Innovative Talents Project (3D Printing Quality Real-time Detection and Quality Prediction Key Technology Research:2018KQNCX343); Zhuhai Mechanical Engineering Dominant Discipline.
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Li, C., Zeng, L., Lin, Y., Gu, F. (2021). Research on Online Monitoring Technology of 3D Printing Faults in Fused Deposition Molding. In: Zhen, D., et al. Proceedings of IncoME-V & CEPE Net-2020. IncoME-V 2020. Mechanisms and Machine Science, vol 105. Springer, Cham. https://doi.org/10.1007/978-3-030-75793-9_10
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DOI: https://doi.org/10.1007/978-3-030-75793-9_10
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