Simulation Research on the Lightning Current Waveform Parameter Estimation
Jiang Xiong Wei · Proceedings of the CSEE · 2009
Return stroke current waveform (RSCW), characterized by the front time, tail time, and current steepness factor, is of great importance for the lightning protection of electric and electronic systems. Focusing on the multi-parameter estimation of RSCW contaminated by measured noise, the paper puts forward a novel numerical algorithm, i.e. Nelder-Mead particle swarm optimization (NMPSO), in which a particle swarm consisting of lightning current character parameters was tackled in the Particle Swarm Optimization (PSO), and each sub-swarm was processed in the Nelder-Mead (NM) algorithm. Therefore, stagnation can be effectively eliminated in the process of PSO. The simulation results of the Heidler’s lightning current expression showed that correlation coefficients of curve match vary from 0.854 6 to 0.999 9 as the signal-noise ratio increasing from 5 dB to 40 dB. In addition, the application of NMPSO in the parameter estimation of the Heidler’s lightning current expression manifests the super noise-resistant ability. As a result, the proposed numerical algorithm with fast and effective properties can be successfully applied to parameter estimation of lightning current waveform in different expressions and to data compression in lightning measurement systems; it is valuable for engineering evaluation and lightning research.