PCB Solder Joint Inspection System PCB 焊點檢測系統

隊伍 Team:氧氣龍 Oxygen Dragon

學校 University:國立成功大學 National Cheng Kung University

指導教授 Advisor:陳中和 Chung-Ho Chen

學生 Student:陳亮州 Liang-Chou Chen、王駿瀚 Jun-Han Wang、曾奕儒 Yi-Ju Tseng

作品連結 Link: GitHub

Team Introduction

We are junior students from the Department of Electrical Engineering at National Cheng Kung University. We are interested in resolving difficulties in our lives with artificial intelligence. In the past, we have suffered a lot from soldering when developing our lab projects. Thus, we have come up with this idea, to make an easy-to-use and efficient way to resolve the soldering issue.

我們是來自成功大學電機工程學系三年級的學生團隊,對以人工智慧解決生活上的難題感到興趣。因為我們在過去實驗焊接時受盡千辛萬苦,痛定思痛,因此發想出這個主題。希望透過比賽,製作出可易於檢測且高效的產品,造福廣大受焊接所苦的人們。

Project Introduction

We plan to use neural network frameworks and the camera on WE-I Plus to capture all solder joints on PCB, then to conduct further analysis on the joints to detect their defects. The system will summarize results to users and increase the efficiency of inspecting PCB solder joints.

我們將藉由類神經網路與鏡頭捕捉PCB上之所有焊點,對其進行焊點品質檢測,標示並分類有瑕疵的焊點,將分析結果呈現予使用者,提升使用者檢測效率。