Title
Defects Classification of Laser Metal Deposition using Acoustic Emission Sensor
Abstract
Laser metal deposition (LMD) is an advanced additive manufacturing (AM) process used to build or repair metal parts layer by layer for a range of different applications. Any presence of deposition defects in the part produced causes change in the mechanical properties and might cause failure to the part. In this work, defects monitoring system was proposed to detect and classify defects in real time using an acoustic emission (AE) sensor and an unsupervised pattern recognition analysis. Time domain and frequency domain, and relevant descriptors were used in the classification process to improve the characterization and the discrimination of the defects sources. The methodology was found to be efficient in distinguishing two types of signals that represent two kinds of defects. A cluster analysis of AE data is achieved and the resulting clusters correlated with the defects sources during laser metal deposition.
Recommended Citation
H. Gaja and F. W. Liou, "Defects Classification of Laser Metal Deposition using Acoustic Emission Sensor," Proceedings of the 28th Annual International Solid Freeform Fabrication Symposium (2017, Austin, TX), pp. 1952-1964, The University of Texas at Austin, Aug 2017.
Meeting Name
28th Annual International Solid Freeform Fabrication Symposium -- An Additive Manufacturing Conference, SFF 2017 (2017: Aug. 7--9, Austin, TX)
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Acoustic emission; Clustering analysis; Deposition defects; Laser metal deposition
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 The University of Texas at Austin, All rights reserved.
Publication Date
01 Aug 2017
