Abstract
In this paper, a computer aided methodology of classification of flaws, which are formed in aluminium alloys during production of elements for car engines with the low-pressure casting method is presented. The flaw identification was performed on the basis of digital recorded data registered by the use of X-ray image analysis method. In order to solve this problem, an elaborated methodology and related computer programmes for X-ray images analysis, as well as the preparation of entrance data for neuronal networks and also the quality cast control were used. The classification results of the best type of every network investigated are presented. Analysing a number of correct classifications of pointed out test data, the classifying problems are evaluated.
| Original language | English |
|---|---|
| Pages (from-to) | 456-462 |
| Number of pages | 7 |
| Journal | Journal of Materials Processing Technology |
| Volume | 167 |
| Issue number | 2-3 |
| DOIs | |
| Publication status | Published - 30 Aug 2005 |
Keywords
- Aluminium alloys
- Cast defects
- Images analysis
- Neural networks
- Technological science
ASJC Scopus subject areas
- Ceramics and Composites
- Computer Science Applications
- Metals and Alloys
- Industrial and Manufacturing Engineering
Fingerprint
Dive into the research topics of 'Computer aided classification of flaws occurred during casting of aluminum'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver