TY - GEN
T1 - Characterizing the Vibro-acoustic Signals of Electromechanical Transmissions for Online Monitoring 3D Printing Process of FDM
AU - Zou, Xinfeng
AU - Li, Zhen
AU - Yang, Chunhua
AU - Gu, Fengshou
AU - Ball, Andrew D.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - Currently, the 3D printing process is characterized by a prolonged printing time, unstable printing quality, and susceptibility to a variety of disruptions. Consequently, it is necessary to propose a method of condition monitoring during the 3D printing process to assure the stable quality of the printed model and to replace operators’ constant observation during the 3D printing process. Since fused deposition modelling (FDM) is one of the most widely used 3D printing techniques, this research focuses on the relationship between the printing process of FDM and vibro-acoustic signals from the electromechanical transmission system, improves coupled equations to illustrate the relationship between the printing velocity and step motor frequencies based on the electromechanical transmission kinematics, and develops an online condition monitoring method as a result. Based on theoretical analysis and data processing, the enhanced coupled equations are proposed to initiate the research. Afterwards, the coupled equations have been validated through experimentation. Lastly, this research investigates whether the vibro-acoustic signal characteristics can be utilized for online monitoring of the FDM 3D printing process. Current studies indicate that vibration signals are more effective than acoustic signals for online condition monitoring of the FDM 3D printing process, and that the proposed technique can be used to effectively monitor the 3D printing process.
AB - Currently, the 3D printing process is characterized by a prolonged printing time, unstable printing quality, and susceptibility to a variety of disruptions. Consequently, it is necessary to propose a method of condition monitoring during the 3D printing process to assure the stable quality of the printed model and to replace operators’ constant observation during the 3D printing process. Since fused deposition modelling (FDM) is one of the most widely used 3D printing techniques, this research focuses on the relationship between the printing process of FDM and vibro-acoustic signals from the electromechanical transmission system, improves coupled equations to illustrate the relationship between the printing velocity and step motor frequencies based on the electromechanical transmission kinematics, and develops an online condition monitoring method as a result. Based on theoretical analysis and data processing, the enhanced coupled equations are proposed to initiate the research. Afterwards, the coupled equations have been validated through experimentation. Lastly, this research investigates whether the vibro-acoustic signal characteristics can be utilized for online monitoring of the FDM 3D printing process. Current studies indicate that vibration signals are more effective than acoustic signals for online condition monitoring of the FDM 3D printing process, and that the proposed technique can be used to effectively monitor the 3D printing process.
KW - Condition monitoring
KW - Electromechanical transmissions
KW - FDM 3D printer
KW - Vibro-acoustic signal
UR - http://www.scopus.com/inward/record.url?scp=85195556964&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-49421-5_50
DO - 10.1007/978-3-031-49421-5_50
M3 - Conference contribution
AN - SCOPUS:85195556964
SN - 9783031494208
T3 - Mechanisms and Machine Science
SP - 615
EP - 627
BT - Proceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2023) - Volume 2
A2 - Ball, Andrew D.
A2 - Wang, Zuolu
A2 - Ouyang, Huajiang
A2 - Sinha, Jyoti K.
PB - Springer Science and Business Media B.V.
T2 - UNIfied Conference of International Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, International Conference on Maintenance Engineering, IncoME-V 2023, International conference on the Efficiency and Performance Engineering Network, TEPEN 2023
Y2 - 29 August 2023 through 1 September 2023
ER -