| Title: | Automated detection of soldering splashes using YOLOv5 algorithm |
| Authors: | Klčo, Peter Koniar, Dusan Hargas, Libor Paskala, Marek |
| Citation: | 2022 International Conference on Applied Electronics: Pilsen, 6th – 7th September 2022, Czech Republic, p. 107-110. |
| Issue Date: | 2022 |
| Publisher: | Fakulta elektrotechnická ZČU |
| Document type: | konferenční příspěvek conferenceObject |
| URI: | http://hdl.handle.net/11025/49861 |
| ISBN: | 978-1-6654-9482-3 |
| Keywords: | hybridní výkonový polovodič;pájecí splash;vizuální kontrola;konvoluční neuronové sítě;YOLOv5 algoritmus |
| Keywords in different language: | hybrid power semiconductor;soldering splash;visual inspection;convolutional neural network;YOLOv5 algorithm |
| Abstract in different language: | This paper deals with automated visual inspection of electronic boards in serial manufacturing of power electronics devices. Soldering splashes generated in the relevant phases of manufacturing can decrease the quality, parameters and lifetime of hybrid power semiconductor modules. Soldering splashes can occur in restricted area of electronic board and must be removed. Automated inspection is provided using neural network YOLO trained on image dataset of electronic boards acquired by authors in SEMIKRON Slovakia company. Implemented method will lead to higher reliability of manufacturing process. |
| Rights: | © IEEE |
| Appears in Collections: | Applied Electronics 2022 Applied Electronics 2022 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| uvod.pdf | 1,61 MB | Adobe PDF | View/Open | |
| Automated_detection_of_soldering_splashes_using_YOLOv5_algorithm.pdf | Plný text | 830,52 kB | Adobe PDF | View/Open |
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