| 研究生: |
陳建穎 Chen, Cheng-Ying |
|---|---|
| 論文名稱: |
智能監控模組於LED集魚燈具之實務研究 Implementation and Research of Intelligent Monitoring Module for LED Fishing Lamps |
| 指導教授: |
沈聖智
Shen, Sheng-Chih |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 系統及船舶機電工程學系 Department of Systems and Naval Mechatronic Engineering |
| 論文出版年: | 2017 |
| 畢業學年度: | 105 |
| 語文別: | 中文 |
| 論文頁數: | 92 |
| 中文關鍵詞: | 智能燈具 、無線監控 、LED集魚燈 、LM-80 、壽命預測 |
| 外文關鍵詞: | Intelligent Lamps, Wireless Monitoring, LED Fishing Lamps, LM-80, Lifetime Prediction |
| 相關次數: | 點閱:95 下載:1 |
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本研究係將智慧監控系統概念應用於LED集魚燈具領域,並針對船用環境進行分析與探討,實際建構最適當之無線傳感網路於現有之LED集魚燈具上,搭配LabVIEW建立人機介面與後端之壽命預測運算。
由於近年來智慧照明的概念日益廣泛,本論文將導入其概念至LED集魚燈具領域,並針對船用環境之需求進行剖析,在無線傳輸通訊端、感測傳輸介面端、終端訊息轉傳端等三部分進行最適性分析,再進行整體無線傳感網路的建置,包含終端之感測器電路配置與訊號讀取、協調端之LabVIEW擷取訊號與人機介面建構,以及兩者間的無線通訊配對,其中,本研究在終端燈具部分,以穩壓模組的方案取代了常見的PWM調光,屏除了可能造成集魚效果不佳的原因,並在協調端程式部分,利用LM-80數據為基礎,進行壽命預測運算,來確保長時間出航之漁業船隻裝設LED集魚燈具的效益。
實驗結果部分:(1)針對實際漁業用船來說,本研究選用ZigBee無線通訊協定來進行整體建構;(2)感測訊號具有相當程度的準確性,電壓最大誤差為0.812%、電流最大誤差為2.5%、溫度最大差值為0.21℃;(3)壽命預測程式在自製之光衰試驗中之預測誤差為0.664%,而以正規之LM-80數據進行壽命預測驗算,預測誤差值皆幾乎小於1%。
In this paper, in order to ensure the economic benefits for deep-sea-fishing, we combine LED fishing lamps with intelligent monitoring module. To evaluate the working environment on the ship, we choose the most suitable sensors and wireless protocol to build the wireless sensor network. The whole system of this research is divided into three parts: (1).Wireless Communication, (2).Coordinator, (3).End-Device.
On the part of wireless communication, we choose ZigBee as the wireless protocol. For the end device, LM317 voltage stabilizer can change the power consumption of LED lamp, thus replace the common dimming method – PWM, which could lead to poor fishing result. For the last part, coordinator, LabVIEW is applied to show the sensing data and calculate the lifetime of LED. Also, the lifetime calculate is based on LM-80 data.
The experiment results prove great appropriate of ZigBee and accuracy of the sensors. In addition, the calculation errors for the LED lifetime program based on LM-80 and the least squares method are almost less than 1%.
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校內:2022-07-01公開