Silicone rubber material is widely used in high-voltage external insulation systems due to its excellent hydrophobicity and hydrophobicity transfer performance. However, silicone rubber is a polymeric material with a poor ability to resist electrical tracking and erosion; therefore, some fillers must be added to the material for performance enhancement. The inclined plane test is a standard method used for evaluating the tracking and erosion resistance by subjecting the materials to a combination of voltage stress and contaminate droplets to produce failure. This test is time-consuming and difficult to apply in field inspection. In this paper, a new and faster way to evaluate the tracking and erosion resistance performance is proposed using laser-induced breakdown spectroscopy (LIBS). The influence of filler content on the tracking and erosion resistance performance was studied, and the filler content was characterized by thermogravimetric analysis and the LIBS technique. In this paper, the tracking and erosion resistance of silicone rubber samples was correctly classified using principal component analysis (PCA) and neural network algorithms based on LIBS spectra. The conclusions of this work are of great significance to the performance characterization of silicone rubber composite materials.
Keywords: laser-induced breakdown spectroscopy; neural network; silicone rubber material; tracking and erosion resistance.