臺灣博碩士論文加值系統

智慧製造技術為當前歐、美、日、韓列為主要發展項目之一，例如德國最先倡導的工業4.0，被認為是以智慧製造為主導的第四次工業革命或革命性的生產方法，旨在藉由充分利用資訊通訊技術和網路空間虛擬系統(Cyberspace virtual system)相結合的手段，將製造業向智慧化轉型。本研究為建構基於雲端之超精密加工系統，以Data Distribution Service (DDS)通訊協定下建立私有雲，運用MySQL資料庫管理系統進行資料的存放，由Python程式語言來編寫Apache與Django作為網頁伺服器的架構平台，利用感測器來擷取加工機內在與外在之加工時相關數據，其中包含聲音、亮度、濕度、振動、光學尺和光學遮斷感測器結合微控制器Raspberry pi來進行接收感測資訊以及發布資訊，而由Django下開發的網頁介面可以存取的資料包括加工條件、加工機環境、分析相關數據、量測數據處理、即時位置擷取裝置(Position acquisition device, PAD)所量測之刀座移動情形等，讓研究人員能夠透過網頁所提供的介面即時檢視工具機狀態及實驗進行過程的相關資料之建立、查詢、與編輯，也使傳統加工機具有通訊能力，而能透過MQTT通訊協定與Node-RED流程編程的視覺化的方式能夠即時呈現出上述所提到的各式數值及轉換的曲線圖以方便研究人員方便觀看，以此證明傳統加工機可以具備有感測與通信能力，也能使傳統加工機改造成智慧機台，來因應未來工業4.0的應用。

The smart manufacturing is one of the major development projects in Europe, the United States, Japan, and Korea. For example, Industry 4.0, which was first advocated by Germany, is considered to be the fourth industrial revolution or revolutionary production method led by smart manufacturing. With the combination technologies of information communication and cyberspace virtual system, the manufacturing industry is expected to be transformed to smart manufacturing. This study aims to build a cloud-based ultra-precision processing system. Base on the Data Distribution Service (DDS) communication protocol, a private cloud is established. The MySQL is employed to develop a database management system for data storage. The web server architecture is accomplished with the Apache server and Django platform by the Python programming language. The web interface can access the sensor’ information from the internal of the machine and external environment, such as sound, light intensity, humidity, vibration, encoder, and photo interrupter. With the Raspberry pi micro-controller, the sensor information can be acquired and published. In addition, the processing conditions, machine environment, analysis data of related research, process of measured data, and the motion of tool holder measured by the real-time position acquisition device (PAD), etc, can be retrieved through the web page. This allows laboratory members to create, query, and edit the data related to process monitoring and experiment. The visualization of the MQTT protocol and Node-RED process programming can instantly present various sensor values and converted line graphs for easy observation during processing, thus proving that the traditional machine could have sensing and communication abilities, and realizing the improvement of the traditional machine into a smart machine to meet the application of Industry 4.0.

摘要 i
ABSTRACT ii
誌謝 iii
目錄 iv
圖目錄 vi
表目錄 viii
第一章 緒論 1
1.1 研究背景 1
1.2 文獻回顧 2
1.3 研究目的 4
1.4 研究方法與流程 4
1.5 論文架構 5
第二章 雲端系統規劃 7
2.1雲端伺服器策劃 7
2.1.1 Data Distribution Service (DDS) 7
2.1.2 雲端系統流程 9
2.1.3 雲端系統架構 10
2.2 雲端伺服器與邊緣裝置 10
2.2.1 邊緣裝置規劃 10
2.2.2 雲端結合邊緣裝置架構 11
2.2.3 邊緣裝置感測器模組 12
第三章 雲端系統硬體建置 13
3.1 伺服器設備 13
3.1.1 伺服器 14
3.1.2 Raspberry pi 15
3.1.3 雙頻無線路由器 16
3.2 加工應用感測器 18
3.2.1 桌上型四軸超精密加工機 18
3.2.2 光學尺 19
3.2.3 訊號擷取裝置 20
3.2.4 陶瓷振動感測器 23
3.2.5 CompactRIO 控制器 24
3.3 環境偵測感測器 25
3.3.1 MCP3008模數轉換器 25
3.3.2 模擬聲級計 26
3.3.4 光敏感測器 27
3.3.5 DHT11數位溫濕度感測器 27
3.3.6 光遮斷器 28
3.3.7 BMP180大氣壓力感測器 29
第四章 雲端系統架構與展示 31
4.1 DDS傳輸 31
4.1.1 Raspberry pi與伺服器模組介紹 31
4.1.2 DDS程式應用 32
4.1.3 DDS發布與訂閱 32
4.1.4 Raspberry pi結合DDS成果 36
4.1.5 Raspberry pi連接感測器 37
4.1.6 伺服器模組化 40
4.1.7光學尺之類比訊號傳輸 41
4.1.8 光學尺之數位訊號傳輸 45
4.2 可視覺化數據 48
4.2.1 Django Web框架 48
4.2.2 Django Web設計成果 48
4.2.3 感測器數據顯示 50
第五章 結論與未來展望 53
5.1 結論 53
5.2 未來展望 54
參考文獻 55

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