The aim of this paper is to give an overview on partial discharges at d c voltage. A model is presented which describes the stochastic discharge process. The model is experimentally verified for internal discharges and for corona in air. In addition, the classification of discharge patterns is discussed. The 3-dimensional histogram describing the number of discharges depending on the discharge magnitude and on the time to the successive discharge is suggested to be used as a base for discharge recognition at d c voltage. Experimental proof is presented to show the strength of this approach.
In this paper the measurement of partial discharges at DC voltage is discussed in order to be used as a tool for diagnosis. A classification method based on the calculation of fractal features is shown, which is illustrated with experiments on artificial defects as well as on industrial components. For the classification of partial discharge pattems at DC voltage fractal features have been found to be useful.
When designing ac insulation systems much knowledge and experience is available concerning partial discharges. However, for dc insulation there is a lack of knowledge of partial discharges and their effect on reliability and lifetime. For this reason we conducted a study on the distribution functions of the discharge magnitude and the time between two discharges. A model has been developed to describe the discharge behavior for dc voltage. The measurement results are in agreement with the proposed model. The extinction voltage of the discharges is close to the ignition voltage. The discharge frequency is mainly determined by the statistical time lag (period between reaching a voltage sufficient to cause breakdown and the breakdown itself). The statistical time lag depends strongly on the test voltage.
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