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In this paper, we present an approach to determining classification of partial discharge (PD) events in Gas Insulated Load Break Switches (GILBS). Probabilistic neural networks (PNN) and the fuzzy C-means (FCM) clustering approach are used as the classification method. Discrete wavelet transform (DWT) is employed to suppress noises in the measured signals of high-frequency current transformers (HFCT)...
This paper proposes an approach to determining classification of partial discharge (PD) events in Gas Insulated Load Break Switches (GILBS). Discrete wavelet transform (DWT) is employed to suppress noises of measured signals by the high-frequency current transformer (HFCT). Three kinds of different defects are designed and placed inside three GILBS individually. For accurately determination of the...
At present, the contribution of partial discharge (PD) to power equipment insulation diagnosis is highly valued all over the world. However, most PD measurements are still carried out in the laboratory. The main reason for this is that the effects of on-field noise suppression are still limited and unsatisfactory. In recent years, among noise suppression methods, wavelet de-noising is the most common...
This paper presents a novel approach based on first-order eigenvalue sensitivity to analyze an autonomous parametric generator (SEPG) under different PF loading conditions. A balanced three-phase induction-motor model is employed to derive the dynamic equations of an isolated SEPG feeding static loads. The proposed method can effectively determine maximum and minimum values of excitation capacitance...
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