研究生: |
莊于萱 Chuang, Yu-Hsuan |
---|---|
論文名稱: |
端銑刀磨耗定量檢測系統 End-milling Cutter Wear Quantitative Inspection System |
指導教授: |
葉哲良
Yeh, J. Andrew 駱遠 Luo, Yuan |
口試委員: |
蔡孟勳
Tsai, Meng-Shiun 鄭志鈞 Cheng, Chih-Chun 曾文鵬 Tseng, Wen-Peng 徐文慶 Hsu, Wen-Ching 黃國政 Huang, Kuo-Cheng |
學位類別: |
碩士 Master |
系所名稱: |
工學院 - 動力機械工程學系 Department of Power Mechanical Engineering |
論文出版年: | 2019 |
畢業學年度: | 107 |
語文別: | 中文 |
論文頁數: | 85 |
中文關鍵詞: | 刀具磨耗 、機械視覺 、三維重建 、量化 、QR碼 、智慧化 |
外文關鍵詞: | Cutter wear, Machine vision, 3D reconstruction, quantify, QRcode, smart machine |
相關次數: | 點閱:1 下載:0 |
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銑削加工為機械製造加工上常見方法之一,然隨加工次數之增加,刀具磨耗區域逐漸擴大,是為影響加工業產品精度及良率之重要因素,儘管已有諸多研究提出不同刀具壽命預估模型來預估磨耗量,期望有助於產線上之刀具工序調整,並且利用國際標準組織訂定之磨耗機制與標準來做規範,卻受限於加工條件之不確定性,仍需倚靠直接之監測系統始能有效對不同磨耗類型採取應對措施。因此,為提出有效能量化磨耗程度之檢測方式,本研究將延續先前所架設之光學系統,透過機械視覺之方法進行磨耗量之分析,並主要從軟體端如邊緣計算、三維重建等演算法強化,以期能達到高準確度且快速完成檢測之需求,同時配合QRcode的使用,將刀具與檢測資料連結,欲打造智慧化檢測機台,以利資料之追蹤進而供與使用者採取相對應的配刀程序。
Milling operation plays an important role in industrial manufacturing process. Wear of the cutting tool is an inevitable result of the metal cutting process, and it will directly affect the quality and yield of products in the factory. In the past decades, there were already many researches providing the predictive models to predict wear region by mathematic formula. Even International Organization for Standardization (ISO) has defined types and standards of wear for us to categorize different wear types. However, due to the uncertainty during machining process, wear monitoring system is necessary to detect tool wear effectively. Therefore, in this thesis, I will work on improving the original machine vision system. Modify the contour profile extracted algorithm and precisely quantify wear level of milling cutter tool as the output computing results. Calibrate the hardware parts to make the whole inspection system become more robust, so as to efficiently match the requirement of practical inspection need. Furthermore, complete a proof of concept for combining the output data with QRcode on every milling cutter tool to realize the concept of Industry 4.0 on making a smart inspection machine.
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