臺灣博碩士論文加值系統

摘 要
本研究實作，利用樹莓派電腦，透過 Python 程式語言來接收、過濾感測元件所提供的數據，
並將所關注的資訊送到遠端內部私有雲資料庫匯整，最終將數據整理並透過網頁方式呈現給。
此研究能夠有效的改善傳統工廠直線型生產線的作業流程，將數值透過數位化的角度提取，讓
資訊更清析、透明化，進而達到 a.發覺產線沒注意的管理缺陷，b.減少人為誤判，c.將所提取
的數據匯整，把繁瑣的統計方式簡化，c.將資訊即時的提供給管理人員(經理、業務…等)，提
升現場與管理人員的連結性

Abstract
In this implementation for research, use Python programming language in RaspberryPi computer to catch and filter data provided at those sensor.
Then It's can sent those data to remote database in internal private cloud,and
organize those data to be display for web browser.
This research can effectively improve the operation process of the traditional
factory, that make the information more clear and transparent,then it can extract
the values through a digital perspective, and then achieve that :
a. Discover the Problem that the production line did not pay attention
b. Misjudgment from people
c. provide the information to the management (manager, business...etc.)in real
time,and improve the connection between the field and the management personnel.

目錄
一. 緒論.................................................................................................................................................................. 9
1.1. 研究動機以及目的................................................................................................................................................. 9
1.2. 論文章節概要....................................................................................................................................................... 11
二. 設備功能與技術說明......................................................................................................................................12
2.1. 樹莓派單板電腦(RASPBERRY PI).................................................................................................................... 12
2.2. I²C 簡介[5]
..................................................................................................................................................... 13
2.3. 雷射測距器(VL53L0X)[10]
.............................................................................................................................. 14
2.4. OPECV 做影像辨識
[1]
..................................................................................................................................... 16
2.4.1. 電腦視覺(Computer Vision CV)
[11]
................................................................................................... 16
2.4.2. 說明 HSV 所定義的項目 ....................................................................................................................... 17
2.5. 序列通訊標準 RS-232
[13]
.................................................................................................................................... 18
2.6. 動態網站伺服器(LAMP)[12]
............................................................................................................................ 20
2.7. PROXMOX [8]
....................................................................................................................................................... 22
三. 各系統架構及規劃..........................................................................................................................................24
3.1. 架構圖 ........................................................................................................................................................... 24
3.1.1. 架構圖(未數位化) ............................................................................................................................... 24
3.1.2. 原架構問題分析 ............................................................... 25
3.1.3. 架構圖(數位化改善) ............................................................................................................................ 25
3.1.4. 改善偵測重點....................................................................................................................................... 25
3.2. 流程圖 ........................................................................................................................................................... 26
3.2.1. 投料區................................................................................................................................................... 26
3.2.2. 影像辨識物件區................................................................................................................................... 27
3.2.3. 磅秤區................................................................................................................................................... 28
四. 基礎環境建置 .................................................................................................................................................29
4.1. 安裝樹莓派(RASPBERRYPI)
[7]
.......................................................................................................................... 29
4.2. 投料區應用
[6]
............................................................................................................................................... 31
4.2.1. 雷射測距器(VL53l0X)硬體安裝以及 16x2 液晶顯示器 ................................................................... 31
4.2.2. 雷射測距器設定程式如下 ................................................................................................................... 32
4.2.3. 雷射測距程式說明............................................................................................................................... 33
4.2.4. 現場人員監看用 LCD 16x2 液晶顯示器程式 .................................................................................... 34
4.2.5. LCD 程式說明....................................................................................................................................... 34
4.3. 影像辨識區[2]
................................................................................................................................................ 35
4.3.1. OpenCV 安裝
[2]
....................................................................................................................................... 35
4.3.2. 硬體設備............................................................................................................................................... 36
4.3.3. 確認與安裝 Python 以及 OpenCV ....................................................................................................... 36
4.3.4. 安裝完後執行測試，檢查執行 OpenCV .............................................................................................. 36
4.3.5. 影像辨識程式....................................................................................................................................... 38
4.3.6. 影像辨識程式說明............................................................................................................................... 40
4.3.7. 模擬物件偵測....................................................................................................................................... 41
4.4. 磅秤區 ........................................................................................................................................................... 42
4.4.1. RS232 偵測數據................................................................................................................................... 42
4.4.2. 硬體設備示意圖................................................................................................................................... 42
4.4.3. 磅秤區程式........................................................................................................................................... 43
4.4.4. 磅秤區程式說明................................................................................................................................... 44
4.5. LAMP 系統建置 .............................................................................................................................................. 45
4.5.1. PVE (Proxmox)虛擬機建置 ................................................................................................................. 45
4.5.2. PHP 接收數據(接收投料數據程式) .................................................................................................... 50
4.5.3. PHP 接收投料區程式說明 .................................................................................................................... 51
4.5.4. PHP 接收影像數據................................................................................................................................ 52
4.5.5. PHP 接收影像程式說明 ........................................................................................................................ 52
4.5.6. 接收磅秤數據程式............................................................................................................................... 53
4.5.7. 磅秤收據接收程式說明 ....................................................................................................................... 54
4.5.8. 資料庫 DataBase 資料狀況 ................................................................................................................ 54
4.5.9. PHP 以及網頁呈現................................................................................................................................ 55
4.6. 系統整合應用實作分析................................................................................................................................ 56
4.6.1. 整合架構說明....................................................................................................................................... 56
4.6.2. 再透過匯整的資料進行分析如下 ....................................................................................................... 57
4.6.3. 表格匯整資料比較 ............................................................. 61
4.6.4. 資料提供管理人員後得知分析結果 ................................................ 61
五.結論與未來發展....................................................................................................................................................62
六.參考文獻 ...............................................................................................................................................................65

[1] CorporationIntel. (2000 年 06 月). OpenCV. 擷取自 https://zh.wikipedia.org/zh-tw/OpenCV (P15)
[2] DurmuşBerkCan. (2021 年 11 月 27 日 ). OpenCV Python Installation for Raspberry Pi. 擷 取 自
https://singleboardblog.com/install-python-opencv-on-raspberry-pi/ (P35)
[3] elinux. (2019 年 12 月 20 日). elinux. 擷取自 https://elinux.org/Main_Page
[4] FoundationSoftwareApache. (1997). Apache. 擷取自 Apache: https://httpd.apache.org/ (P19)
[5] IrazabalJean-Marc, & BlozisSteve . (2003 年 3 月 24 日 ). AN10216-01 I2C MANUAL. 擷取自
https://web.archive.org/web/20170110165928/http://www.nxp.com/documents/application_note/AN1021
6.pdf (P12)
[6] johnbryanmoore. (2017 年 02 月 18 日 ). VL53L0X_rasp_python. 擷取自
https://github.com/johnbryanmoore/VL53L0X_rasp_python (P31)
[7] LtdPiRaspberry. (2012). Raspberry Pi Documentation. 擷 取 自 Raspberry Pi:
https://www.raspberrypi.com/documentation/computers/getting-started.html (p29)
[8] Proxmox. (2004). Proxmox. 擷取自 Proxmox: https://www.proxmox.com/en/about (P22)
[9] SemiconductorsNXP. (2015 年 12 月 25 日). I²C Bus. 擷取自 https://zh.wikipedia.org/wiki/I%C2%B2C
[10] STMicroelectronics. (2021). VL53L0X. 2021 擷 取 自
https://www.st.com/content/ccc/resource/technical/document/datasheet/group3/b2/1e/33/77/c6/92/47/6
b/DM00279086/files/DM00279086.pdf/jcr:content/translations/en.DM00279086.pdf (P13)
[11] WIKI. (2021 年 12 月 17 日 ). HSV. 擷取自 WIKI-HSV: https://zh.m.wikipedia.org/zhhant/HSL%E5%92%8CHSV%E8%89%B2%E5%BD%A9%E7%A9%BA%E9%97%B4 (P15)
[12] WIKI. (2021 年 2 月 7 日). LAMP. 擷取自 WIKI-LAMP: https://zh.wikipedia.org/wiki/LAMP (P19)
[13] WIKI. (2021 年 11 月 12 日). RS-232. 擷取自 WIKI-RS-232: https://zh.wikipedia.org/wiki/RS-232 (P17)
[14] WIKI. (2022 年 7 月 24 日 ). http. 擷 取 自 WIKI-HTTP:
https://zh.wikipedia.org/wiki/%E8%B6%85%E6%96%87%E6%9C%AC%E4%BC%A0%E8%BE%93%E5%8D%8F
%E8%AE%AE (P19)
[15] WIKI. (2022 年 2 月 18 日). I2C. 擷取自 WIKI-I2C: https://zh.wikipedia.org/zh-tw/I%C2%B2C (P12)
[16] WIKI. (2022 年 5 月 21 日). Linux. 擷取自 WIKI-Linux: https://zh.wikipedia.org/zh-tw/Linux (P19)
[17] WIKI. (2022 年 6 月 23 日). Mariadb. 擷取自 WIKI-Mariadb: https://zh.wikipedia.org/wiki/MariaDB (P21)
[18] WIKi. (2022 年 1 月 22 日). Mysql. 擷取自 WIKI-Mysql: https://zh.wikipedia.org/zh-tw/MySQL (P21)
[19] WIKI. (2022 年 7 月 1 日 ). www. 擷取自 WIKI-WWW:
https://zh.wikipedia.org/wiki/%E4%B8%87%E7%BB%B4%E7%BD%91