Cable hybrid line fault distance measuring method for k-NN algorithm based on waveform similarity
A technology for mixing cables and line faults, applied in directions such as fault locations, can solve the problems of complex steps, influence of power supply reliability, and heavy workload, achieving good ranging effect, high ranging result accuracy, and saving investment.
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Embodiment 1
[0039] Example 1: Now assume that a single-phase grounded metal fault occurs on the main line 8.75km away from the M terminal, the initial phase angle of the fault is 90°, the fault transition resistance is 70Ω, the simulation sampling frequency is 1MHz, and the zero mode collected by the distance measuring device at the M terminal is used The current waveform, the wavelet coefficient waveform obtained after wavelet decomposition and reconstruction, and the wavelet coefficient waveform under different fault conditions in the simulated historical samples are calculated using the correlation analysis formula (1), and the first three similarities are obtained. The fault distance corresponding to the waveform data. Defining weights for waveform similarity-based fault locating D To use correlation analysis to measure the similarity of two signals. According to the fault distance represented by the first three waveform data with the highest similarity and combined with its differen...
Embodiment 2
[0040] Embodiment 2: Now assume that a single-phase grounded metal fault occurs on the main line 13.65km away from the M terminal, the initial phase angle of the fault is 60°, the fault transition resistance is 30Ω, the simulation sampling frequency is 1MHz, and the zero mode collected by the distance measuring device at the M terminal is used The current waveform, the wavelet coefficient waveform obtained after wavelet decomposition and reconstruction, and the wavelet coefficient waveform under different fault conditions in the simulated historical samples are calculated using the correlation analysis formula (1), and the first three similarities are obtained. The fault distance corresponding to the waveform data. Defining weights for waveform similarity-based fault locating D To use correlation analysis to measure the similarity of two signals. According to the fault distance represented by the first three waveform data with the highest similarity and combined with its diff...
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