本文針對電纜接頭做出兩種類型各三組之破壞電壓試驗，試圖從中找出共同的老化規則。首先將所產生之局部放電，經由雜訊抑制、資料轉換、特徵萃取再套用移動平均法後，找出特徵值負放電區域的放電總和-相位分布之相位重心，具有相同的現象產生，重心隨著資料筆數的增加有漸漸往第三象限(180度)靠攏的趨勢，並且在要擊穿之前產生一個轉折的現象。
接著使用k平均法將資料分群，將其定義為老化中期與後期兩部分，用以訓練決策樹。最後發現特徵值正放電區域的放電總和-相位分布之相位重心、負放電區域的放電總和-相位分布之相位重心和相位解析圖譜之分形維度被決策樹選用的機率很高，高達64 %，將以上三個特徵值用以訓練決策樹得到的整體測試成功率為A1：92 %、A2：87.6 %、A3：95.3 %、B1：97.7 %、B2：91.3 %和B3：95.2 %。最後選用A3之決策樹模型作為評估電纜接頭老化狀態之代表，其交叉比對之整體成功率的平均值高達83.47%，使完成評估電纜接頭絕緣狀態之研究。

This thesis has finished the breakdown voltage tests for two types of defects each of them have three groups. Try to find out the general rules from the tests after noise inhibited, data transformation, feature extraction and using moving average method. We find out that the feature of the sum of discharge from negative region - center of phase distribution has the same phenomenon in all the defects. The center towards to the third quadrant (180 degrees) as the data increased and turned again before breakdown.
Then using k-means to cluster data and defined them as medium or late term of aging that use them to train the decision trees. Find out that the sum of discharge from positive region - center of phase distribution, the sum of discharge from negative region - center of phase distribution and fractal dimension have the rate of 64% to be used. Use the features above we can get the overall success rate of A1: 93.2 %, A2: 87.1 %, A3: 94 %, B1: 93.8 %, B2: 89.7 % and B3: 93.7 %. At last, the decision tree from A3 to be chosen as the representative for insulation status assessment of cable joints. The rate of it after cross-comparison is up to 83.47 %. To finish the development for the insulation status assessment of high voltage cable joints.

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