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| 研究生： |
蔡陳杰 Tsai, Chen-Chieh |
|---|---|
| 論文名稱： |
以 Centernet 為基礎開發 AOI 輔助系統之研究 A Study of Centernet Based AOI Assistant System Development |
| 指導教授： |
黃文吉
Hwang, Wen-Jyi |
| 口試委員： |
張寶基
Chang, Pao-Chi 周賜福 Joesph Arul |
| 口試日期： | 2021/08/03 |
| 學位類別： |
碩士 Master |
| 系所名稱： |
資訊工程學系 Department of Computer Science and Information Engineering |
| 論文出版年： | 2021 |
| 畢業學年度： | 109 |
| 語文別： | 中文 |
| 論文頁數： | 52 |
| 中文關鍵詞： | 自動光學檢測 、元件檢測 、深度學習 、邊緣計算 |
| 英文關鍵詞： | Centernet, Automated optical inspection, Component detection, Deep learning, Edge computing |
| 研究方法: | 實驗設計法 |
| DOI URL： | http://doi.org/10.6345/NTNU202101299 |
| 論文種類： | 學術論文 |
| 相關次數： | 點閱：54 下載：8 |
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自動光學檢測(AOI)為結合電腦視覺與自動化等多種技術的自動檢測方法，並且廣泛使用於產品製造的品質管理上，而元件檢測是自動光學檢測中的重要檢測項目之一。近年來，由於工業產業的變化，產品生產走向了少量多樣化，而在檢測上也改以邊緣運算的裝置運行，因此除了傳統元件檢測要求的準確率外，理想的元件檢測方法還必須要運算複雜度夠低與模型小才能在邊緣運算裝置上運行，而常見的元件檢測方法並不能完全達到這些要求。
本論文使用Centernet作為新建立的AOI元件檢測系統的核心演算法。其優點為應用廣泛以及容易簡化與縮小模型，讓模型足夠輕量在工廠上的邊緣運算裝置上運行，且在通用物件檢測有良好的檢測效果。而本論文完成之元件檢測系統能夠快速偵測出元件，以及將其系統應用於嵌入式系統上，以達到工業上減少成本的需求，也可以應用在客製化的元件檢測上。
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