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論文名稱(外文):Analysis of Broken Ear Straps on The Mask Production Line Using Machine Vision
外文關鍵詞:Mask machineultrasonic weldingoptical identification
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When traditional semi-servo mask generation equipment produces masks, it takes a lot of time to adjust and is driven by a power motor, so it is more difficult to adjust. Sometimes it takes more than half a day to adjust or repair. , So now the market has been changed to a fully servo-controlled mask machine as the mainstream, and with the automatic correction technology to make the concession smoother, save time and save time, you don’t need to keep people staring at the operation of the machine. Be careful of the fabric offset, which results in scraps of hundreds of meters of fabric. Generally speaking, the shortcomings of traditional mask machines have been greatly improved. However, this type of mask machine lacks the ability to identify whether the mask earbands are actually welded, and therefore have this shortcoming And there is the research concept of this thesis.
The research of this thesis is based on the concept of common mask machines on the market. It uses a visual recognition system to determine whether the mask is welded correctly to avoid unnecessary losses. It uses the recognition software matlab to analyze and calculate the yield value. So that the direction of machine transformation later.
After analyzing by matlab, use imaging observation to change the ultrasonic welding position and wave time, and even change the ultrasonic welding height, energy and current. It can also be observed whether it is because the track is too narrow that the mask is reflexed and cannot be welded. The problems, improve these problems, and achieve the highest performance of the machine.

誌 謝 i
摘 要 ii
Abstract iii
目錄 v
圖目錄 viii
表目錄 x
第一章、緒論 1
1.1研究背景與動機 1
1.2 研究背景 2
1.3文獻探討 3
1.4論文架構 8
第二章、口罩生成設備相關研究 9
2.1半伺服口罩機設備介紹 9
2.1.1半伺服口罩機布料架說明 10
2.1.3半伺服口罩機耳帶熔接設備說明 14
3.1視覺辨識理念介紹 18
3.2視覺辨識架構介紹 19
3.3雲台伺服馬達控制補正 20
3.5雲台架構介紹 20
3.6程式編碼 24
3.7影像分析介紹 25
3.8視覺辨識程式碼 27
3.9程式碼細部介紹 28
3.10影像前處理流程 31
3.11分段線性灰階變換 33
3.12基本線性灰階變換 35
3.13均衡處理 36
3.14大背光盒 41
3.15大背光盒材料 42
第四章、研究總結與未來方向 45
4.1研究成果 45
4.2研究貢獻 45
4.3未來研究方向 45
參考文獻 46
附錄 49
燈盒尺寸圖 49
實驗數據 50

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