Automated microstructural analysis of titanium alloys using digital image processing
Campbell, A. and Murray, P. and Yakushina, E. and Marshall, S. and Ion, W. (2017) Automated microstructural analysis of titanium alloys using digital image processing. IOP Conference Series: Materials Science and Engineering, 179 (1). 012011. ISSN 1757-899X (https://doi.org/10.1088/1757-899X/179/1/012011)
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Abstract
Titanium is a material that exhibits many desirable properties including a very high strength to weight ratio and corrosive resistance. However, the specific properties of any components depend upon the microstructure of the material, which varies by the manufacturing process. This means it is often necessary to analyse the microstructure when designing new processes or performing quality assurance on manufactured parts. For Ti6Al4V, grain size analysis is typically performed manually by expert material scientists as the complicated microstructure of the material means that, to the authors knowledge, no existing software reliably identifies the grain boundaries. This manual process is time consuming and offers low repeatability due to human error and subjectivity. In this paper, we propose a new, automated method to segment microstructural images of a Ti6Al4V alloy into its constituent grains and produce measurements. The results of applying this technique are evaluated by comparing the measurements obtained by different analysis methods. By using measurements from a complete manual segmentation as a benchmark we explore the reliability of the current manual estimations of grain size and contrast this with improvements offered by our approach.
ORCID iDs
Campbell, A. ORCID: https://orcid.org/0000-0002-4439-3630, Murray, P. ORCID: https://orcid.org/0000-0002-6980-9276, Yakushina, E. ORCID: https://orcid.org/0000-0001-6498-4502, Marshall, S. ORCID: https://orcid.org/0000-0001-7079-5628 and Ion, W. ORCID: https://orcid.org/0000-0003-0693-5942;-
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Item type: Article ID code: 60525 Dates: DateEvent1 March 2017Published14 February 2017AcceptedSubjects: Technology > Engineering (General). Civil engineering (General) > Engineering design Department: Faculty of Engineering > Design, Manufacture and Engineering Management
Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset Management
Strategic Research Themes > Advanced Manufacturing and Materials
Strategic Research Themes > Measurement Science and Enabling TechnologiesDepositing user: Pure Administrator Date deposited: 25 Apr 2017 13:26 Last modified: 11 Nov 2024 11:41 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/60525