| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 814566 | Rare Metal Materials and Engineering | 2016 | 7 Pages |
Grain size is one of the crucial parameters in the microstructure analysis of high strength aluminum alloy. This information is commonly derived based on manual processes. However, these manual processes may take long time and error are prone to occur. Nowadays?the rapid development of the digital image processing and the pattern recognition technologies provides a new methodology for the quantitative metallographic analysis. Artificial intelligence utilized in realizing automatic metallographic analysis can overcome the drawbacks of the manual processes. In the present paper we presented a new method of digital image processing for determining the grain sizes of the metallographic images. To derive the grain sizes of the digital metallographic images, the digital image processing was applied to extract grain boundary by proposing a new edge detection algorithm based on fuzzy logic. Extensive metallographic images with different qualities were tested to validate this method. Practical application cases were presented here. The grain size was calculated in accordance with American Society for Testing Material (ASTM) standards.
