Method for Separating Multiple Partial Discharge Sources in Space Based on Model Parameter Identification
The effective identification and separation of multiple partial discharge(PD)source signals is the key to PD detection,location and analysis.For this reason,a method of spatial multiple partial discharge source separation based on model parameter identification was proposed.Firstly,the ultra-high frequency(UHF)signal was modeled using autoregressive moving average model and high order cumulant parameter estimation method;then the spectrum of the signal was reconstructed according to the model parameters,and the characteristic frequency of the signal was selected based on Fisher separability;finally,U HF signal types were classified based on the selected characteristic frequency and radial basis function neural network.The simulation study verified the effectiveness of the method in spectrum reconstruction and signal classification of UHF signals.The accuracy of multiple partial discharge sources separation in unknown partial discharge source signals with SNR greater than 10 dB is more than 75％,which has good application value.
万方数据
维普
