Diagnostic Methods for Composite Insulators with Biological Growth
Composite insulators have a number of advantages compared to conventional insulators, but the fact that they are more prone to aging is a major drawback. For instance, biological growths, like algae and fungi, have been found to colonize composite insulators, and possibly effecting the insulation performance. So far there is a lack of diagnostic methods capable of detecting material changes of composite insulators in the field, and developing new diagnostic methods has thus become very important.
One of the main aims of the work presented in this thesis was to elucidate on the influence of biological growth on the electrical performance of composite insulators. To do this, fungi originating from insulators installed in Sweden were grown on silicone rubber insulators and material samples in a climate chamber. The performance of the insulators were studied through leakage current measurements conducted occasionally during a period of one and a half years and wet flashover voltage measurements at the end of the test. It was found that presence of growth reduced the average flashover voltage by 30 %, and increased the leakage currents by 3-4 times, compared to clean reference insulators. Insulators colonized in service showed a lower influence of growth.
In the field of diagnostics, laser-induced fluorescence spectroscopy has been explored as a tool for detection of changes on surfaces of composite insulators. Measurements were conducted in laboratory as well as remotely outdoors. These revealed that the fluorescence response was influenced by properties like the hydrophobicity of the surface, presence and type of growth, material composition. As an example, it was found that algae readily could be identified from a distance of 60 m through fluorescence of chlorophyll.
To characterize the distribution of (bio)contamination, tools based on digital image analysis were applied. The initial experiments were carried out by using photographs of flat material samples with fungal growth, but later the investigations were expanded to parts of real insulators as well. Measures for characterizing growth patterns were explored, and methods for estimating the length of creepage distance not covered by growth were investigated. Finally, techniques for automatic identification of insulator sheds, based on Hough transform, were developed. This allowed for use of a shed model, taking surface curvature into account when estimating covered area.
digital image analysis
laser-induced fluorescence (LIF)