CVT lightning impulse voltage inversion based on high-frequency wavelet entropy and low-frequency signals

The non-linear components contained in CVT make it impossible for CVT to obtain the approximate voltage waveform when measuring lightning impulse voltage. To get the approximate waveform, this paper uses the wavelet entropy of the high-frequency signal and the low-frequency signal as the input of the BP neural network, then the primary side lightning impulse voltage waveform can be inverted. Moreover, the wavelet decomposition is used to filter out the signals higher than the frequency points in the inverted voltage waveform. Based on the field test data of CVT lightning shock, the results show that the method reduces the overshoot of the waveform at the rising edge after the inversion, which can provide a reference for the subsequent equipment of CVT to judge the lightning impulse signal.