XCT was introduced on a unit- and micro-scale level. Certain frequency ranges, window sizes, time spans, and energy density concentrations were found to correlate to the formation of certain internal defects. A variety of signal processing methods were found to facilitate feature extraction through techniques such as thresholding and background noise reduction. Simultaneous use of imaging methods provided a way to study melt pool dynamics in 3D and detect sub-surface defects in printed components with sizes as small as 50 μm.Īcoustic sensors are used to record acoustic signals generated from the Additive Manufacturing process, which are then analysed to provide critical information about the formation of internal defects in an additively manufactured part.
The studies showed that IR cameras were found to show sub-surface and internal defect formation tendency in the part with sizes up to 1000 μm, as well as detect vapour plume and powder spatter ejection in the Additive Manufacturing process X-ray imaging was found to identify depressions and other melt pool characteristics. Ex-situ testing techniques are introduced as methods for verification of results gained from in-situ monitoring data.
In ‘In-situ Monitoring of Sub-surface and Internal Defects in Additive Manufacturing: A Review’, representation and analysis of the acquired in-situ data from both imaging and acoustic methods is discussed, as well as the means of data processing. Raw acoustic emission signals can correlate to particular defect mechanisms using methods of feature extraction. Acoustic methods rely on acoustic sensing technologies and signal processing methods to acquire and analyse acoustic signals, respectively. Many studies have been conducted that prove the reliability of imaging methods in monitoring the Additive Manufacturing process and build area, as well as detecting defects. Imaging methods consist of visual and thermal monitoring techniques, such as optical cameras, infrared (IR) cameras, and X-ray imaging. In this research paper, application of both imaging and acoustic methods for the in-situ detection of sub-surface and internal defects is discussed. The research was published as ‘In-situ Monitoring of Sub-surface and Internal Defects in Additive Manufacturing: A Review’ in the journal Materials & Design. Researchers from Composite Materials and Mechanics Laboratory, Mechanical and Aerospace Engineering Department, New York University, Tandon School of Engineering, have released a paper covering in-situ monitoring methods for the Additive Manufacturing process which can help evaluate the quality of material deposition and develop methods of in-situ intervention.
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