Seam tracking in automated welding
| Autor: | Keyvan Kasiri, Ahmed Gawish, Paul Fieguth |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Brightness Ground truth Computer science business.industry 010401 analytical chemistry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ComputerApplications_COMPUTERSINOTHERSYSTEMS Image processing 02 engineering and technology Welding 01 natural sciences Edge detection 0104 chemical sciences law.invention 020901 industrial engineering & automation Robustness (computer science) law Computer vision Artificial intelligence business |
| Zdroj: | SMC |
| DOI: | 10.1109/smc.2017.8122572 |
| Popis: | With the growing number of automated welding systems present throughout manufacturing, achieving high precision is naturally a key objective. The alignment of weld tip to weld seam, particularly in very long welds (such as in pipes), is a technical challenge in which computer vision has much to offer. This paper introduces a real-time methodology for weld-seam tracking. The key challenge associated with the weld tracking problem is to accurately locate the seam and welding tip; that is, to define image features which allow the seam and tip edges to be identified. An efficient edge detection method based on steerable filters is proposed to have a robust edge extraction in different conditions of noise and illumination. The image processing precision is experimentally verified through comparison with ground truth data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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