On-line decision tree-based insulation assessment employing mathematical morphology filters for HV cables

In this paper a new approach is given for insulation assessment of HV cables based on investigating the void size and/or remained insulation thickness (RIT), while the void is considered as the partial discharge source. The proposed decision tree based algorithm has well kept its capability in classifying the void size under different conditions of geometrical properties of the void such as size, depth and location; cable characteristics such as age and temperature; and also environmental noise. The procedure includes four stages which are, signal de-noising, PD detection, feature generation and compensation and finally void classification. In the first stage, the prerequisite task of de-noising is performed by a filter based on Mathematical Morphology (MM). PD detection stage is carried out based on mathematical morphology functions, too. In the feature generation stage, a compensation procedure is employed, in order to diminish the effect of pulse propagation along the cable on the PD features used for classification. Finally, in the last stage, void classification is done by Decision tree. Simulation results have shown high accuracy of the proposed insulation assessment method. In addition, in the stages of noise reduction and PD detection, performances of the algorithms are examined by experimental data which is recorded in the field.