Open AccessDataset Citra Papan Sirkuit Tercetak dengan Komponen yang Terbakar
Author(s) -
Iwan Awaludin,
Trisna Gelar,
Muhammad Rizqi Sholahuddin,
Gina Melinia,
Irvan Kadhafi,
Rezky Wahyuda Sitepu
Publication year - 2021
Publication title -
building of informatics, technology and science
Language(s) - English
Resource type - Journals
eISSN - 2685-3310
pISSN - 2684-8910
DOI - 10.47065/bits.v3i3.1025
Subject(s) - printed circuit board , computer science , data set , set (abstract data type) , artificial intelligence , software , obstacle , impression , computer vision , computer hardware , engineering drawing , computer graphics (images) , engineering , world wide web , operating system , political science , law , programming language
The application of artificial intelligence, especially in the automatic optical inspection of printed circuit boards or PCBs, is increasingly being carried out by researchers. Unfortunately, the data used to train and test artificial intelligence models is synthetic data. Printed circuit boards in good condition are imaged and then changed by software to give the impression of defects. In addition, the type of damage is limited to pre-operation, namely when the PCB is not yet operational. After the PCB is operational, damage can occur, for example, burned components. Until now, there is no data set of PCB images with burned components. This study, therefore, explores data retrieval techniques that can produce the required data set. This data collection technique includes hardware setup and PCB data sources. Based on the exploration results, it is concluded that a trinocular digital microscope with high resolution can produce sharp PCB images. The obstacle that arises is the difficulty of getting PCBs with burned components. The solution was obtained by referring to the PCB repair video from the Youtube channel. Several data were collected and tested with EfficientDet with 90% mAP.