遗传算法和BP神经网络在电机故障诊断中的应用研究

人工智能方法在电机故障诊断中的应用，使得电机故障能够得到及时准确的预测和诊断，保障了电机的安全运行。介绍了BP神经网络及遗传算法的基本原理及组成结构，针对BP神经网络容易陷入局部极小点及收敛速度慢的问题，利用遗传算法对BP神经网络的权值和阀值优化，改善了BP神经网络的诊断性能；通过GA-BP网络对电机的三种故障模式进行了诊断识别，其实验仿真结果表明：无论是在诊断速度上还是诊断精度上，GA-BP神经网络诊断性能都比单独的运用BP网络有了很大提高。

Application Research on Genetic Algorithm and BP Neural Network in Motor Fault Diagnosis

Artificial intelligence method was applied in motor fault diagnosis, which made motor fault that can be predicted and diagnosed in time, and ensured the safe operation of motor. The principle and composition of BP neural network and genetic algorithm were introduced, In view of the problem that BP neural network was easily to fall into local minimum point, The diagnosis performance of BP neural was improved by using genetic algorithm optimization weight and threshold value of BP neural network; A result shows that GA-BP network better than BP network on diagnosis Speed and accuracy by simulation experiment of motor fault diagnosis.