SA-APSO Algorithm and Its Application in Ultrasonic Location of Partial Discharge in Transformer Oil Academic Article uri icon


  • 2018, Xi'an High Voltage Apparatus Research Institute Co., Ltd. All right reserved. In allusion to the basic particle swarm optimization algorithm local search optimization ability is poor and it is easy to premature convergence, an improved PSO, which integrate simulated annealing idea into the adaptive particle swarm optimization algorithm, is proposed. It is named simulated annealing-adaptive particle swarm optimization algorithm (SA-APSO), based on the adaptive particle swarm optimization, it integrates the simulated annealing idea and accept the optimal value with certain probability. SA-APSO can effectively enhance the global searching ability and overcome the premature convergence phenomenon. The simulation results show that the SA-APSO algorithm is superior to the basic PSO in the accuracy and stability of the results. And its application in location of partial discharge in transformer oil is calculated, the results with the basic PSO and adaptive particle swarm optimization are compared. The results show that based on SA-APSO transformer oil partial discharge-ultrasonic positioning method can realize the accurate global localization and stable result, the synthetic error less than 3.7 mm.

published proceedings

  • Gaoya Dianqi/High Voltage Apparatus

author list (cited authors)

  • Xu, Y., Wang, Q., Li, Z., Li, Z., & Lu, M.

complete list of authors

  • Xu, Y||Wang, Q||Li, Z||Li, Z||Lu, M

publication date

  • December 2018