Ardila Rey, Jorge Alfredo

Partial discharge (PD) monitoring is one of the most used tools for diagnosing the condition of electrical equipment and machines that operate normally at high voltage levels. Ideally, PD identification can be easily done if there is a single source acting over the electrical asset during the measurement. However, in industrial environments, it is common to find the presence of multiple sources acting simultaneously, which hinders the identification process, due to sources of greater amplitude hiding the presence of other types of sources of lesser amplitude that could eventually be much more harmful to the insulation system. In this sense, the separation of PD through the use of clustering techniques allows individual source recognition once they have been clearly separated. This article describes the main clustering techniques that have been used over time to separate PD sources and electrical noise. The results obtained by the different authors in the utilization of each technique demonstrates good performance in terms of separation.

Electrical trees are one of the main mechanisms of degradation in solid polymeric insulation leading to the failure of high voltage equipment. They are interconnected networks of hollow tubules typically characterized from two-dimensional (2D) projections of their physical manifestation. It is shown that complete characterization requires a three-dimensional (3D) imaging technique such as X-ray computed tomography (XCT). We present a comprehensive set of parameters, quantitatively characterizing two types of tree topology, conventionally known as bush- and branchtype. Fractal dimensions are determined from 3D models and from 2D projections, and a simple quantitative relationship is established between the two for all but dense bush trees. Parameters such as number of nodes, segment length, tortuosity and branch angle are determined from tree skeletons. The parameters most strongly indicative of the differences in the structure are the number of branches, individual channel size, channel tortuosity, nodes per unit length and fractal dimension. Studying two stages of a bush tree's development showed that channels grew in width, while macroscopic parameters such as the fractal dimension and tortuosity were unchanged. These parameters provide a basis for tree growth models, and can shed light on growth mechanisms.