研究生: |
陳慶明 CHING-MING CHEN |
---|---|
論文名稱: |
應用決策樹機制於即時性評估交鏈聚乙烯絕緣狀態之研究 Real-time Insulation Status Assessment of XLPE Based on Decision Tree Scheme |
指導教授: |
吳瑞南
Ruay-Nan Wu |
口試委員: |
張宏展
Hong-Chan Chang 謝宗煌 Tsung-Huang Hsieh |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電機工程系 Department of Electrical Engineering |
論文出版年: | 2010 |
畢業學年度: | 98 |
語文別: | 中文 |
論文頁數: | 69 |
中文關鍵詞: | 局部放電 、交鏈聚乙烯 、絕緣狀態診斷 、決策樹 |
外文關鍵詞: | partial discharge, cross-linked polyethylene, insulation Status diagnosis, decision tree. |
相關次數: | 點閱:192 下載:2 |
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地下電纜常用之絕緣材料為交鏈聚乙烯(cross-linked polyethylene, XLPE),由於地下電纜若因絕緣劣化而發生故障,會導致經濟上的損失以及安全上的危害,故為了有效預防地下配電系統事故的發生,在新設地下電纜同時裝置一套局部放電之即時監測系統,長期監控地下電纜之絕緣狀況,達到預防事故發生的效果。
本文的分析對象為交鏈聚乙烯切片的劣化試驗資料,其試驗資料於台灣科技大學高壓實驗室進行高壓加速劣化試驗量測而得,經由電腦程序將其訊號濾波與化簡,將化簡後的資料進行資料轉換並利用特徵萃取找出能判別其絕緣劣化狀態的特徵值,本文使用的特徵為分別是放電總合之區域平均放電量及其斜率曲線與區域平均放電量,其特性分別為各試驗區域平均放電量相似度極高、斜率曲線的轉折特性與區間極值差的階梯狀上升特性;最後利用決策樹機制歸納其特徵值並產生if-then規則進而建立絕緣診斷的即時判斷規則。
決策樹模型包含六個決策節點與十個葉節點,其決策樹對測試資料即時判斷的成功率,初期平均成功率為95.6%,中期平均成功率則有89.8%,末期平均成功率則是81.3%。
The cross-linked polyethylene(XLPE) is the general insulation materials for underground cable. However, it might break down when the cable start to insulation deterioration and then will cause the economic loss and the damage. To perfectly prevent the damage of underground distributed system, this research set up a set of on line monitoring system of partial discharge(PD) to prevent these damages happened.
This thesis is about the slices test of XLPE and made the high voltage and accelerated deterioration test in high voltage laboratory in NTUST. The next step is that to filter and simplified the signal and going to the data switch and further to use feature extraction methods to figure out the feature data of insulation status. This research uses three kinds of feature data that the characteristics are the high Similarity of district average discharge of each test data and the turning properties of slop curve and the stair rises properties of interval extremum deviation. The final step is to use the decision tree scheme to organize the district average discharge, slope curve and interval extremum deviation three feature data and then find the if-then rules further more to set up the on line insulation state diagnosis rules.
The decision tree consists of six decision nodes and ten leaf nodes. The accuracy of real-time insulation status diagnosis about testing data are 95.6% during early stage of degradation、89.8% during middle stage of degradation and 81.3% during final stage of degradation.
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