| Autor: |
Nils Ellendt, Fabian Fabricius, Anastasiya Toenjes |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Applied Sciences, Vol 11, Iss 13, p 6086 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2076-3417 |
| DOI: |
10.3390/app11136086 |
| Popis: |
Additive manufacturing processes offer high geometric flexibility and allow the use of new alloy concepts due to high cooling rates. For each new material, parameter studies have to be performed to find process parameters that minimize microstructural defects such as pores or cracks. In this paper, we present a system developed in Python for accelerated image analysis of optical microscopy images. Batch processing can be used to quickly analyze large image sets with respect to pore size distribution, defect type, contribution of defect type to total porosity, and shape accuracy of printed samples. The open-source software is independent of the microscope used and is freely available for use. This framework allows us to perform such an analysis on a circular area with a diameter of 5 mm within 10 s, allowing detailed process maps to be obtained for new materials within minutes after preparation. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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