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研究生:陳彥斌
研究生(外文):Chen, Yen-Bin
論文名稱:主動式散熱機制設計與研製之研究
論文名稱(外文):Study on the Design and Development of an Active Cooling System
指導教授:李 永 隆
指導教授(外文):Lee, Yung-Lung
口試委員:李明輝洪兆宇紀岍宇盧久章何正榮孔健君李 永 隆
口試委員(外文):Lee, Ming-HueiHung, Chao-YuJi, Chien-YuLu, Jiu-ZhangHo, Jeng-RongKung, Chien-ChunLee, Yung-Lung
口試日期:2015-01-05
學位類別:博士
校院名稱:國防大學理工學院
系所名稱:國防科學研究所
學門:軍警國防安全學門
學類:軍事學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:中文
論文頁數:91
中文關鍵詞:熱導管致冷晶片小波類神經網路適應性小波類神經網路控制器滑動模式控制適應性模糊滑動控制
外文關鍵詞:Heat PipesThermo Electric CoolerWavelet Neural NetworksAdaptive Wavelet Neural Network ControllerAdaptive Fuzzy Sliding Control SystemSliding Mode Control System
相關次數:
  • 被引用被引用:2
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  • 收藏至我的研究室書目清單書目收藏:1
在電子產品日益精密且其核心晶片運算速度大幅度提升之狀況下,致使多工高效能晶片需在狹隘密閉且無對流之高溫環境下運作,進而造成產品內部之熱沈效應劇增,產品的可靠度與壽期因而受到影響。據此,如何設計一有效的散熱系統以確保電子產品正常運作,為現今電子產品在應用上之關鍵技術。目前結合導熱管之散熱技術己被推廣使用,但屬被動式散熱方式,無法依據熱源熱能大小適應性調整散熱速度,進而影響散熱效能。本研究以NI-PXI系統為基礎架構,結合熱導管與致冷晶片,據以設計一新型主動式智慧型散熱控制系統,藉以解決晶片在狹小密閉且無對流環境下之長距離散熱問題。
此外本研究以相位陣列雷達尋標器之主動式散熱裝置設計為對象,提出結合熱導管與致冷晶片之主動式散熱機制,以三種智慧型控制系統為基礎,分別為適應性模糊滑動控制系統,滑動模式控制系統與適應性小波類神經網路控制器;用於解決非線性熱傳系統之控制問題。其中適應性小波類神經網路控制器及強健補償控制器所構築而成之控制器可用來近似理想控制器,而小波類神經網路的參數則由最陡坡降法所推導出之適應性控制律,具即時控制性能;另強健補償控制器則用來決解理想控制器與小波類神經網路控制器之間近似誤差,確保控制迴路之穩定性。經實驗驗證,本文所提之熱導管結合致冷晶片散熱架構可較傳統銅管之散熱架構提升48%散熱效能,另所提之主動式控制器架構於實驗中結果亦顯示,其相較傳統控制器可獲得較佳之控制性能。未來可將所提之控制器架構提供民生、醫療、軍事與工業上之應用,以解決關鍵散熱技術開發之問題。

The high-performance multi-chip needs to work in a narrow, closed and high temperature environment without convection because the sophisticated electronic products with core chip of high operation speed are developed greatly, and that will increase deeply the heat sink effect inside the products. The reliability and life of products will be influenced due to the above condition. As a result, the key technique in the application is to design an effective cooling system to ensure the normal operation of electronic products. Now, the utilization of heat pipe cooling system which is a passive cooling technique has been promoted extensively. It cannot modify the heat dissipation speed appropriately according to the size of heat source and that will influence the effectiveness of heat dissipation. In this paper, the NI-PXI system combined with the heat pipe and the thermoelectric cooling chip is used to design a new active intelligent cooling control system to overcome the heat dissipation problems of long distance produced by the chip working in the narrow, closed and high temperature environment without convection.
Furthermore, the proposed method is applied on the active cooling device of phased-array radar seeker and three theories of intelligent control systems are used to solve the controlling problems of nonlinear heat transfer system. They are the adaptive fuzzy sliding control system, the sliding mode control system and the adaptive wavelet neural network controller, respectively. The controller made by the adaptive wavelet neural network controller and the robust compensation controller can be approximated to an ideal controller. The parameters of wavelet neural network are using the adaptive controlling rules developed by the gradient steepest descent method and which has the real-time control function, and the robust compensation controller is used to solve the approximation error between the ideal controller and the wavelet neural network controller to ensure the stability of control loop. The experiment results verify that the proposed method can increase the dissipation effectiveness of 48% compared with the traditional dissipation structure of copper pipe and the structure of active controller also has the better controlling ability than the traditional controller. In the future the proposed structure of controller can be applied on the people's livelihood, medicine, military and industry for solving the heat dissipation problems.

目錄

誌謝 i
摘要 ii
ABSTRACT iii
表目錄 vii
圖目錄 viii
符號說明 x
1. 緒論 1
1.1 研究動機與目的 1
1.2 文獻回顧 2
1.3 論文架構 6
2. 結合導熱管與致冷晶片之散熱機制建立與實驗 7
2.1 硬體架構 7
2.2 軟體程式 16
2.3 致冷晶片與導熱管熱傳模式 18
2.4 實驗方法 24
2.5 實驗結果分析 29
2.6 小結 35
3. 智慧型控制器於散熱機制之驗證 36
3.1 智慧型控制系統概述 36
3.2 主動式散熱系統及致冷晶片輸出之動態方程式 37
3.3 滑動模式控制系統設計 38
3.4 適應性模糊滑動控制系統設計 42
3.5 定義模糊控制法則 43
3.6 適應性模糊滑動控制演算機制 47
3.7 近似誤差邊界值估測器設計 51
3.8 適應性小波神經網路控制器設計 52
3.9 小波類神經網路架構及訓練法則 54
3.10適應性小波神經網路學習法則 57
3.11強健補償器設計 59
3.12實驗架構 62
3.13結果與分析 63
4. 結論與建議 66
4.1 研究結論 66
4.2 未來研究方向 67
參考文獻 68
附錄A 74
個人著作 75
自傳 78

表目錄

表2.1硬體架構本文實驗設備規格 9
表2.2實驗型式 11
表2.3散熱模組(Cooling Module) 組成元件表 13
表2.4控制程式各部分運算功能表 16
表2.5散熱端組成元件規格表 23
表2.6實驗條件 28
表2.7總熱阻 31
表3.1模糊控制規則(Fuzzy Table) 44

圖目錄

圖2.1 硬體實驗設備 7
圖2.2 主動式散熱裝置系統說明圖 8
圖2.3 硬體實驗設備放大電路圖 10
圖2.4 四種長距離主動式散熱系統方式(Type a~d )硬體架構 15
圖2.5 Labview 程式碼 16
圖2.6 實驗流程圖 17
圖2.7 致冷晶片尺寸圖[12,32] 19
圖2.8 導熱管蒸發與冷凝端圖 20
圖2.9 散熱系統鯺片與風扇詳細尺寸 21
圖2.10 溫度量測點分佈圖 26
圖2.11 導熱管(Heat Pipe) and實心銅管(Copper Bar)串聯式熱阻流相圖 27
圖2.12 散熱系統熱阻圖(a) Type-a ; (b) Type-b ; (c)Type-c ; (d)Type-d 30
圖2.13 散熱系統熱阻狀態圖 32
圖2.14 四種型式各量測點溫度響應曲線圖(a) Type-a ; (b) Type-b ; (c)Type-c ;           (d)Type-d 34
圖3. 1 滑動模式控制控制器應用於主動式散熱機制圖 39
圖3. 2 適應性模糊滑動控制器應用於主動式散熱機制圖 42
圖3. 3 輸入模糊變數 之歸屬函數 45
圖3. 4 輸入模糊變數 之歸屬函數 46
圖3. 5 輸出模糊變數 之歸屬函數 46
圖3. 6 適應性小波神經網路控制器架構圖 52
圖3. 7 小波類神經網路(WNN)架構圖 54
圖3. 8 量測溫度點分佈 62
圖3. 9 滑動模式控制器應用於主動式散熱機制之控制響應圖 64
圖3. 10 適應性模糊滑動控制器應用於主動式散熱機制之控制響應圖 64
圖3. 11 適應性小波神經網路控制器之控制響應圖 65
圖3. 12 傳統類比控制器之控制響應圖 65
圖4. 1 應用主動式散熱機制於民生、醫療、軍事、工業領域圖 67


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