High-resistance-ground fault detection method based on wavelet transform and neural network for power distribution network
A technology of high-resistance ground fault and neural network, which is applied in the direction of fault location, fault detection according to conductor type, and electrical measurement, etc., can solve threats to the stable operation of the power system and personal safety, reduce the reliability of power grid power supply, and equipment protection leapfrog trips, etc. problem, achieve the effect of avoiding catastrophic forgetting, increasing detection reliability and efficiency, and good generalization ability
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[0032] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0033] Please refer to figure 1 , the present invention provides a kind of distribution network high-impedance ground fault detection method based on wavelet transform and neural network, comprising the following steps:
[0034] Step S1: collecting the current signal of the distribution network line to be detected;
[0035] Step S2: adopt db4 wavelet as mother wavelet, carry out discrete wavelet transform to line current signal, and obtain reconstruction waveform;
[0036] Step S3: the neural network parameter of evolution is set;
[0037] Step S4: using the reconstructed waveform as the input of the evolved neural network, calculating the Manhattan distance between the input and the kth neuron of the evolution layer, the degree of activation of the kth neuron and the error between the output and the expected value;
[0038] Step S5: If the activatio...
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