| 研究生: |
王耀成 Yao-Cheng Wang |
|---|---|
| 論文名稱: |
運用類神經網路於工業製程影像定位之研究 A Study of Image Navigation in Industrial Process by Artificial Neural Network |
| 指導教授: | 黃衍任 |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 機械工程學系在職專班 Executive Master of Mechanical Engineering |
| 論文出版年: | 2018 |
| 畢業學年度: | 106 |
| 語文別: | 中文 |
| 論文頁數: | 98 |
| 中文關鍵詞: | 機器視覺 、工業4.0 、自動化系統 、類神經網路系統 |
| 外文關鍵詞: | Vision Machine, Industry4.0, Automated System, Neural Network |
| 相關次數: | 點閱:22 下載:0 |
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隨著科技進步與市場型態的改變,自動化生產已經廣泛應用在各種不同的行業,為了更加提升自動化系統在製程上的生產效率,德國於2013年提出工業4.0的高科技計畫,而工業4.0是指將現有的工業技術與市場銷售進行整合,透過物聯網(Internet of Things)與大數據(Big Data)分析來進行即時的狀態監控,建立具有適應能力的智能型工廠。
本研究利用類神經網路系統快速計算的功能,將自動化影像系統處理的流程以智慧型的方式來進行數值的計算,建立一套能提高生產效率且具有二維條碼辨識功能的影像系統,並實際探討影像系統與類神經網路系統未來發展的可能性。
As technology advances and changes in market patterns, automated production has been widely used in various industries, in order to further enhance the automation system’s production efficiency in the process, Germany proposes a high-tech project for Industry 4.0 in 2013, Industry4.0 refers the integration of existing industrial technology and marketing,through the IE of things and big data for real-time status monitoring, build a smart factory with adaptability.
This study uses a neural network system fast calculation function, The process of automated systems perform numerical calcilations in a smart way, bulid an automated systems have barcode recognition function and improves production efficiency, practical exploration development of image systems and neural network systems in the future.
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