International Journal of Artificial Intelligence Research
Vol 6, No 1.1 (2022)

Development of PCB Defect Detection System Using Image Processing With YOLO CNN Method

Santoso, Agus Dwi (Unknown)
Cahyono, Ferry Budi (Unknown)
Prahasta, Brendi (Unknown)
Sutrisno, Imam (Unknown)
Khumaidi, Agus (Unknown)



Article Info

Publish Date
08 Oct 2024

Abstract

Inside the equipment there are many electronic components such as resistors, transistors, capacitors and so on. When used in the production of electronic equipment, PCBs are very influential in the manufacture of these electronic devices, for example, when there are only a few broken or damaged PCB paths, the electronic device cannot be operated properly. So it is very important in the PCB Quality Check process to check whether there is damage to the PCB or not. Usually in PCB inspection only direct checking is used in the conventional way. Therefore, in this study, the author tries to create and analyze a PCB flaw checking tool with the help of a camera that has a high revolution to replace human vision to make it easier and save costs. The application of this PCB checking tool uses a technology called a laptop and a camera. With these two technologies, Image Processing can be used to detect objects using the OpenCv and Tensorflow libraries. PCB flaw detection tool with the help of Image Processing with the YOLO Convolutional Neural Network method to help determine broken paths and drill holes on the PCB

Copyrights © 2022






Journal Info

Abbrev

IJAIR

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

International Journal Of Artificial Intelligence Research (IJAIR) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics of Artificial intelligent Research which covers four (4) ...