Three-phase inverter fault diagnosis based on optimized neural networks
The problem that how to use hierarchical genetic algorithm to determine the structure and parameters of neural networks was studied. Utilized the two grade coding structure of the hierarchical genetic algorithm to solve the ancient problem that when optimize the neural networks structure, connection weights, threshold at the same time, the efficiency was low. Furthermore, an improved adaptive hierarchical genetic algorithm was educed, and it improved the shortage of the normal adaptive hierarchical genetic algorithm. At last, the improved adaptive genetic algorithm is used to the fault diagnosis of three-phase inverter, the simulation result shown the method was correct and applied.
hierarchical genetic algorithm neural networks three-phase SPWM inverter fault diagnosis
Fan Bo Dong Ming Zhao Jie Zhang Qiang
The Missile College Air Force Engineering University Shan xi, San yuan, China
国际会议
太原
英文
482-485
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）