地下電纜接頭的絕緣事故是當今電力工程和學術界極力改善的重要議題，隨著各界採納局部放電於高電壓設備的試驗項目之中，電纜接頭的維護和診斷將會是迫切且棘手的問題，原因在於地下電纜系統的接頭數量眾多，若以現今的局部放電檢測儀來工作，其所需的維護人力和成本相當高昂。本文提出一套可長期安置於電纜接頭的局部放電監測模組，此監測模組由峰值檢知電路和數位信號處理器構成，負責將局部放電感測器的信號轉換成放電演進圖譜，並可就地進行簡易的特徵萃取和絕緣診斷，所得資料將定時傳送至主控站電腦，進行儲存管理、分析處理與數據顯示。
本文共有三組直線接頭的局部放電試驗資料，此資料先經過資料轉換和特徵萃取後進行絕緣狀態之分析。文中將特別探討文獻對於相位解析法的正負放電區域定義，並提出改善方法。同時引用多個具有相對大小的放電參量，例如分形維度、放電相位區域、及其統計分布量，使分析規則適用於不同量測設備和場所。資料處理程序可分成離線和即時模式，在離線模式時使用既有的試驗數據進行分析，以建立絕緣診斷規則，而在即時模式定時量測局部放電信號，並依據先前的絕緣診斷規則，進行即時性的絕緣狀態診斷。
絕緣狀態的診斷規則是藉由決策樹分析找出各特徵值間隱藏的關係，當中利用特徵值轉折和離異值分析定義訓練用類別的歸屬值，以及使用基尼索引值定義屬性資料的分割條件。決策樹建模方式採用資訊獲利作為屬性選擇指標，用於決定節點分割時選用的屬性，並使用事前修剪法減少複雜度。由結果得知，各案例的末期辨識率為案例一100%、案例二88%、及案例三84%。此代表由數個決策規則獲得的絕緣狀態診斷具有相當成效，適合用於分散式的局部放電監測模組。

In recent years, to improve the failure of the insulation of underground cable joints becomes the important issue. The test of partial discharges (PDs) was adopted for high voltage apparatus by many companies. The maintenance and diagnosis of cable joint is getting instant and difficult due to the mass of joints in the underground cable systems. It would be expensive with labor and expense to carry out by the recent partial discharge analyzer. This study proposed a long-term placement of PD monitoring unit at cable joints. It is composed of peak detection circuit and DSP (Digital Signal Processor), for acquiring and converting PD signals of sensors into discharge sequence data, and providing the data to computer for the data storage, analysis and display.
Three PD data of underground cable joints were utilized in this paper. In the feature extraction, the discharge region of phase resolved analysis in the reference was interpreted and the improvement was provided. In addition, many discharge quantities were adopted in this paper, such as fractal dimension, discharge phase region, and statistic value. These features still are feasible in the different place. The data process was divided into two parts, off-line and real-tine modes. In the off-time mode, the establishment of the diagnostic rules is performed by the previous data. In the real-time mode, the measurement of partial discharge signal and the diagnosis by the rules are carried out automatically.
The insulation status diagnostic rules are the hidden relation between the features which were discovered by the decision tree method. The class of data was divided by feature turning analysis and outlier analysis. The cut condition was calculated by Gini index method. The information gain was utilized to choose the attribute of the node in the developing of decision tree. The pre-pruning method was used to reduce the complexity of the tree. In the result, both case 1 and 2 have higher success ratio than 80%, excepted lower in case 1. The success ratio of in the midterm and final term are follows, case 1 is 88% and 100%, case 2 is 87 and 88%, case 83% and 84%. Hence, the insulation status diagnosis made by several rules provides sufficient result. These decision rules are suitable for partial discharge monitoring unit (PDMU).

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