Study on Improved Particle Swarm Optimization Algorithm and Its Application

25 fault types of controlled rectifier device are analyzed. A special fault classification method is proposed according to the fault voltage waveforms of rectifier. To enhance the performance of particle swarm optimization (PSO), a novel PSO with disturbance (DPSO) is put forward by introducing an evolution speed factor in standard PSO. Simulation results and comparisons with standard PSO show that the searching efficiency and quality are improved effectively. Finally, DPSO is applied in neural network fault diagnosis modeling. Simulation and experiment study demonstrate that the proposed technique is low time consuming with high fault identification rate.