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系統識別號 U0026-0907201521415500
論文名稱(中文) 電磁熱療系統之自調式模糊溫度控制與調適性網路模糊推論溫度預估模型建置
論文名稱(英文) The Establishment of Self-Tuning Fuzzy Temperature Control and Adaptive Network-Based Fuzzy Inference Temperature Prediction Model for Electromagnetic Thermotherapy System
校院名稱 成功大學
系所名稱(中) 電機工程學系
系所名稱(英) Department of Electrical Engineering
學年度 103
學期 2
出版年 104
研究生(中文) 林國恩
研究生(英文) Guo-En Lin
學號 N26020224
學位類別 碩士
語文別 中文
論文頁數 112頁
口試委員 指導教授-戴政祺
召集委員-王冠智
口試委員-黃世杰
口試委員-尤崇智
中文關鍵字 電磁熱療  自調式模糊控制  比例因子  調適性網路模糊推論  類神經網路 
英文關鍵字 Electromagnetic Thermotherapy  Self-Tuning Fuzzy Logic Controller  Scale Factor  Adaptive Network-Based Fuzzy Inference System  Neural Network 
學科別分類
中文摘要 電磁熱療係以高頻感應加熱器產生交變磁場,在感磁性的金屬針具上產生渦電流進行加熱,達到組織部位治療所需之特定溫度,為確保殺死腫瘤細胞並避免溫度過熱,對溫度的準確控制要求嚴謹。於環境變動導致不確定的加熱模型影響溫度控制,故本文設計自調式模糊控制器,用以改善醫療應用的干擾,準確控制針具的加熱溫度,進行安全治療;另建置以調適性網路模糊理論推論系統溫度預估模型,透過訓練有限元素法所建置的加熱資料庫,來進而重新建構出可於醫療過程中準確預估溫度之生物模型,輔以溫度控制器達到即時預測並掌控溫度動態之效果。經驗證,在使用本系統導入之自調式模糊控制器以及調適性網路模糊推論模型,於模擬病患呼吸時胸腹部導致之加熱距離變動下,治療溫度最大誤差小,且系統具有準確預估即時溫度變化的性能。
英文摘要 Electromagnetic thermotherapy uses a high frequency induction heating machine to generate heat for tumor tissues treating. The induction heating machine produces an electromagnetic field that induces currents on medical needles. The currents heat the medical needles to a specific temperature that is required for treating a tissue area. Accurate control of temperature is crucial to ensure that it is high enough to kill the tumor cells while not overheating the needles. This paper designed a self-tuning fuzzy logic controller (STFLC) that could improve the heating performance in medical applications under interferences and accurately control the temperature of the needles in order to perform safe treatments. This was designed by considering the dynamically environmental factors that will result in the uncertain heating model affecting temperature control. Furthermore, this paper built a temperature prediction model based on an adaptive network-based fuzzy inference system (ANFIS). It was trained by the heating database, which was generated by the finite element method (FEM) model to reconstruct the biomodel that was capable of accurate prediction of temperature in the treatment process. The ANFIS models could assist a temperature controller to effectively make real-time predictions and control temperature. The STFLC and the ANFIS models went through successful testing in experiments simulating the heating distance variation in the abdominal region during patient breathing. The maximum error of the treatment temperature was small and the system was shown to be capable of accurately predicting the change in real-time temperature.
論文目次 目錄
摘 要 I
Extended Abstract II
誌謝 VIII
目錄 IX
圖目錄 XII
表目錄 XVII
第一章 緒論 1
1-1 研究背景 1
1-2電磁熱燒灼簡介 2
1-3 國內外文獻回顧 4
1-4 研究動機與目的 6
1-5 論文架構 7
第二章 感應加熱系統原理及分析 8
2-1前言 8
2-2電磁感應原理 8
2-3感應加熱特性 10
2-3-1渦流損 10
2-3-2相對導磁係數 10
2-3-3 磁滯損 11
2-4串聯諧振轉換器 11
2-4-1全橋串聯諧振轉換器電路架構 13
2-4-2全橋串聯諧振轉換器操作原理及分析 14
2-4-3 全橋串聯諧振轉換器控制手法 16
第三章 控制器設計 18
3-1前言 18
3-2模糊控制系統 18
3-2-1 模糊概念 18
3-2-2 模糊控制器架構 20
3-2-3 模糊化與解模糊化介面 20
3-2-4 模糊知識庫與模糊推論 23
3-2-5 模糊控制器設計 25
3-3自調式模糊控制系統 29
3-3-1 自調式模糊控制器調變方法 29
3-3-2 量化因子與比例因子 30
3-3-3比例因子自調式模糊控制器架構 32
3-3-4 比例因子自調式模糊控制器設計 32
第四章 模型設計 39
4-1模型簡介 39
4-2有限元素分析模型 41
4-3調適性網路模糊推論系統模型 49
4-3-1 模糊與類神經網路 49
4-3-2 模糊模型與控制架構分析 50
4-3-3 調適性網路模糊推論系統模型架構 52
4-3-4 調適性網路模糊推論系統模型設計 54
第五章 系統架構與實驗結果分析 60
5-1系統架構 60
5-2系統硬體 62
5-2-1 閘極隔離驅動電路 62
5-2-2 一次側CT全波整流濾波電路 62
5-2-3 溫度感測電路 65
5-3系統軟體 66
5-3-1 系統操作流程 66
5-3-2溫度控制流程 69
5-3-3 人機介面設計 71
5-4系統性能指標分析 72
5-5實驗與結論 74
5-5-1 溫度控制預估模型 74
5-5-2 即時溫度預估模型 82
5-5-3 變動溫度設定溫控實驗 90
5-5-4 變動加熱距離溫控實驗 95
5-5-5模擬病患呼吸加熱距離變動溫控實驗 100
第六章 結論與未來展望 104
6-1結論 104
6-2未來展望 105
參考文獻 106
自述 XIX
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