Multi-layer ultrasonic imaging of as-built Wire + Arc additive manufactured components
Zimermann, Rastislav and Mohseni, Ehsan and Lines, David and Vithanage, Randika K.W. and MacLeod, Charles N. and Pierce, Stephen G. and Gachagan, Anthony and Javadi, Yashar and Williams, Stewart and Ding, Jialuo (2021) Multi-layer ultrasonic imaging of as-built Wire + Arc additive manufactured components. Additive Manufacturing, 48 (Part A). 102398. ISSN 2214-8604 (https://doi.org/10.1016/j.addma.2021.102398)
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Abstract
Non-Destructive Evaluation (NDE) of metal Additively Manufactured (AM) components is crucial for the identification of any potential defects. Ultrasonic testing is recognised for its volumetric imaging capability in metallic components and high defect sensitivity. However, conventional ultrasonic techniques suffer from challenges when deployed on components with curved and non-planar geometries, such as those often encountered in AM builds. The body of work introduces the concept of inspection of Wire+Arc Additive Manufacture (WAAM) components from their non-planar as-built surface, eliminating the requirement for post-manufacturing machining. In-situ or post-manufacturing inspection is enabled via an autonomously deployed conformable phased array roller-probe deploying Synthetic Aperture Focusing Technique (SAFT)-surface finding and multi-layer adaptive Total Focusing Method (TFM) algorithms, for fully focussed imaging of the as-built WAAM component. The concept of the imaging approach is demonstrated by inspection, through the as-built surface, of two titanium WAAM components, one containing reference bottom-drilled holes, and the other with intentionally introduced Lack of Fusion (LoF) defects. The TFM images of the WAAM components feature sufficient Signal-to-Noise Ratio to enable defect detection along with strong agreement against reference X-Ray CT data, confirming the competency of the approach for volumetric or layer-specific inspection of as-built WAAM components.
ORCID iDs
Zimermann, Rastislav, Mohseni, Ehsan ORCID: https://orcid.org/0000-0002-0819-6592, Lines, David ORCID: https://orcid.org/0000-0001-8538-2914, Vithanage, Randika K.W. ORCID: https://orcid.org/0000-0002-1023-2564, MacLeod, Charles N. ORCID: https://orcid.org/0000-0003-4364-9769, Pierce, Stephen G. ORCID: https://orcid.org/0000-0003-0312-8766, Gachagan, Anthony ORCID: https://orcid.org/0000-0002-9728-4120, Javadi, Yashar ORCID: https://orcid.org/0000-0001-6003-7751, Williams, Stewart and Ding, Jialuo;-
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Item type: Article ID code: 78785 Dates: DateEvent31 December 2021Published13 October 2021Published Online8 October 2021AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
Strategic Research Themes > Advanced Manufacturing and Materials
Technology and Innovation Centre > Sensors and Asset ManagementDepositing user: Pure Administrator Date deposited: 03 Dec 2021 11:33 Last modified: 19 Nov 2024 01:16 URI: https://strathprints.strath.ac.uk/id/eprint/78785