A genetic based algorithm for digitally recorded impulse parameter estimation

This work describes a new method for estimating the mean curve of impulse voltage waveforms that are recorded during impulse tests. In practice, these waveforms are distorted by noise, oscillations and overshoot. The proposed method is based on Genetic algorithms (GAs) optimization technique. The problem is formulated as an estimation problem. The genetic algorithm technique is used to solve the formulated problem. The method is tested using a simulated data of practical waveforms. Effects of a number of samples and data window size are studied. Effects of GAs parameters and operators, such as population size, crossover, mutation probabilities, niching and fitness functions are also studied. Results are reported and discussed.