Application of improved genetic algorithm in ultrasonic location of transformer partial discharge

Detecting and locating the partial discharge point inside the transformer is one of the key measures to ensure the normal operation of transformer. In this paper, an improved genetic algorithm (GAICM) based on improved cross-model was proposed. In this algorithm, crossover operator and mutation operator are improved, and an adaptive model is introduced. GAICM was tested by classical test functions. The test results showed that GAICM has good convergence speed and optimization ability. Meanwhile, GAICM was applied to the ultrasonic localization of transformer partial discharge, and its positioning effect was compared with the location effect of genetic algorithm, simulated annealing algorithm and particle swarm optimization algorithm. The experimental result showed that the application of GAICM to the ultrasonic localization of the transformer partial discharge is more effective.