基于模糊神经网络的电力变压器故障诊断研究

将模糊控制和神经网络理论相结合,通过遗传算法对其参数进行优化,有效地解决了常规模糊理论不能自学习和神经网络算法易陷入局部极小、收敛速度慢等缺点,并对其应用于电力变压器故障诊断进行了仿真,实例仿真结果表明该算法具有较快的收敛速度和较高的计算精度,故障诊断结果证实了该算法应用于电力变压器故障诊断的有效性。

Research of fault diagnosis based on fuzzy neutral network to power transformer

In this paper,the fuzzy control and neural network theory are combined,the parameters of the fuzzy neural network are optimized by genetic algorithm,effectively improve the defects of ordinary fuzzy theory,i.e.,not self-learning,and the defects of neural network algorithm,i.e.,easy to fall into local minimum and slow convergence speed.The application of the fuzzy neural network to power transformer fault diagnosis is simulated,the simulation results of practical examples show that the convergence speed of t...