Hybrid regrouping PSO based wavelet neural networks for characterization of acoustic signals due to surface discharges on H.V. glass insulators
A hybrid algorithm combining particle swarm optimization with wavelet radial basis function neural network is presented. To detect, identify and characterize the acoustic signals due to discharge activity and hence differentiate abnormal operating conditions from the normal ones. A regrouping technique is used to help the swarm escape from the state of premature convergence. Results indicate that the proposed approach can make a quick response and yield accurate solutions. Comparisons with the existing conventional networks show that the proposed approach is efficient and reliable.
acoustic signal glass insulator dry bands rbf-nn surface discharge and wavelet transform pso and regpso