In this paper, an effort has been made to evaluate the online condition of arc contacts as a vital component of interruption chamber in high voltage puffer type SF6 circuit breakers. The relationship between eroded mass caused by short-circuit current interruption and different thermal stress indices such as transferred electrical charge, current squared, and arc energy is investigated, by performing many experiments with different current amplitudes and arcing times. It is demonstrated that none of the known indices can solely determine mass erosion caused by the current interruption. Therefore, the equations including two of defined parameters are proposed to evaluate mass erosion. The method using arc energy and transferred electrical charge owns the highest accuracy in evaluating mass loss. However, considering the complexity of arc voltage measurements, a second method using current and arcing time can be also utilized. In addition, the development of erosion during the lifetime of arc contacts is studied. It is shown that arc roots tend to form on new uneroded areas of the contacts during current interruption, resulting in different erosion rates between the first few and subsequent interruptions due to change of morphology of the contacts after the first few switching operations.

This paper presents a dynamic modeling approach to analyze pollution flashover of silicone rubber insulators. Pre-flashover conditions can be used to represent analytical formulations for different stages of dry band arcing activities on the surface of polluted insulator. In this paper, effects of dust deposit as non-soluble deposit density (NSDD) are investigated on dynamic behavior of partial arcs on surface of insulators by means of a proposed multi-arcs modeling approach. It is shown that analytical formulations of dynamic resistance of surface pollution can be used to analyze different mode of arcing as unstable and stable. Real data of leakage current (LC) and flashover voltage (FOV) of polluted insulator are used to make correlation with analytical multi-arcs formulations. The proposed analytical multi-arcs model is based on an artificial neural network (ANN) which is able to predict the LC and FOV of the insulator in real-time monitoring. In addition, effects of pollution resistance as variable surface conduction and thickness of pollution layer are investigated on LC and FOV of the insulators. It is shown that the proposed multi-arcs representation has a closer correlation with real testing data in comparison of previous single-arc and multi-arcs models.