Abstract
The change and development of leakage current (LC) during the flashover process of insulators are closely related to the discharge process. Characteristic quantities of LC play an important role in the identification and prediction of ice-covered flashover development stages. In this paper, the feature extraction method for LC of ice-covered insulator is discussed based on the shape characteristics of chaotic attractor. Firstly, the power spectrum and the largest Lyapunov exponent are used to analyze the LC of ice-covered insulator qualitatively and quantitatively, which confirmed positive chaotic features during the flashover process. On this basis, the LC is reconstructed in phase space. To solve the problem that the attractor in the high-dimensional space cannot be observed in the phase space reconstruction, the principal vector analysis method is used to project the high-dimensional reconstruction vector into the three-dimensional space to reduce the dimension. Finally, the evolution law of chaotic attractor in each stage of LC under different pollution degree is analyzed and discussed. The results show that the LC of ice-covered insulator has obvious characteristics of attractor shape at different stages of pollution, and is sensitive to the degree of pollution and each stage of development. So the shape of the attractor of LC has important application value for the identification of pollution flashover state and prediction of pollution flashover process of ice-covered insulators.
Highlights
T He ice flashover accident caused by the insulator icing is one of the main reasons for the insulator fault
In order to extract features that can reflect the essence of ice flashover from complex leakage current (LC) signal, researchers have done a lot of work and proposed a variety of feature extraction methods, including empirical mode decomposition ((EMD)) [4]–[6], ensemble empirical mode decomposition (EEMD) [7] [8], wavelet transform (WT) [9] [10], and harmonic analysis (HA) [11]–[13]
In order to solve the problem that the attractor in high dimensional space cannot be observed in phase space reconstruction, We propose to use the main feature analysis method to solve the problem
Summary
T He ice flashover accident caused by the insulator icing is one of the main reasons for the insulator fault. In order to extract features that can reflect the essence of ice flashover from complex LC signal, researchers have done a lot of work and proposed a variety of feature extraction methods, including empirical mode decomposition ((EMD)) [4]–[6], ensemble empirical mode decomposition (EEMD) [7] [8], wavelet transform (WT) [9] [10], and harmonic analysis (HA) [11]–[13]. The HA method is simple and fast in the feature extraction of LC and the accuracy of feature extraction is constantly improving, there is still no unified standard for harmonic selection, which cannot completely match the discharge activity on the surface of the insulator For this kind of nonlinear LC with complex influencing factors, nonlinear time series analysis (such as chaos, fractal theory.) is the research method that can better describe essential characteristics and inherent changes. The collected LC waveforms under different pollution levels which are shown in Fig. 3 (a), (b), and (c)
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