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Non-linear Ultrasonic Spectroscopy of 3d Printed Metallic Samples

: Prevorovsky, Z.; Krofta, J.; Kober, J.; Chlada, M.; Kirchner, A.


Insight 61 (2019), No.3, pp.157-161
ISSN: 1354-2575
ISSN: 0007-1137
Journal Article
Fraunhofer IFAM, Institutsteil Pulvermetallurgie und Verbundwerkstoffe Dresden ()

Current metal additive manufacturing (AM) technologies imply complicated processes, with many variable parameters determining their performance and the quality of the resulting product. Process optimisation requires feedback from nondestructive evaluation (NDE) of the additively manufactured parts. The presence of a complicated internal structure and complex shapes and geometries are limiting factors in the application of standard, preferably online, NDE techniques for quantitative assessment of process-related defects such as irregular internal structure, porosity, etc. In this study, potential non-linear elastic wave spectroscopy (NEWS) methods were tested to classify two types of artificially created defect in Ti-6Al-4V prismatic samples fabricated by an electron beam melting (EBM) system. Two series of samples with variable internal defects were tested: samples with central circular defects (missing material gaps) and samples with gradually growing stochastic porosity. Each group of samples also contained a fully compact sample for comparison. Additional ultrasonic NEWS procedures were then tested to classify the variability of defects. A relatively simple experimental facility with two piezoelectric transducers allowed samples to be analysed and the results recorded. The best results, documented in this paper, were obtained using two modifications of the non-linear wave modulation spectroscopy (NWMS) procedure. One group was successfully classified with two mixed excitation frequencies; slopes of amplitude-dependent inter-modulation sidebands identified samples with growing defect thickness. For the second group, longer chirp excitation was used mixed with signals of constant frequency and/or without any mixing. Growing dispersed stochastic porosity was successfully classified using these methods. The results of NEWS tests indicate that selected NEWS procedures can also be used for online AM monitoring.