基于Elman神经网络的齿轮箱故障诊断

基金项目:

河南理工大学电气工程与自动化学院，河南焦作454000

详细信息

Gear box fault diagnosis based on Elman neural networ

School of Electrical and Automation Engineering, Henan Polytechnic University, Jiaozuo 454000, China

摘要: 针对基于传统BP神经网络的齿轮箱故障诊断方法存在的收敛速度慢、精度不高等问题，提出了一种基于Elman神经网络的齿轮箱故障诊断模型。该模型以齿轮箱特征向量为输入、故障类型为输出，通过改进遗传算法对Elman神经网络的权值和阈值进行优化，将优化后的Elman神经网络用于齿轮箱故障诊断。仿真结果表明，该故障诊断模型加快了网络训练速度，提高了齿轮箱故障诊断的准确度和精度。
- 齿轮箱 /
- 故障诊断 /
- Elman神经网络 /
- 遗传算法
Abstract: For problems of slow convergence speed and low precision existing in gear box fault diagnosis method based on traditional BP neural network, a gearbox fault diagnosis model based on Elman neural network was proposed. In the model, feature vectors are taken as input information and fault types as output information. An improved genetic algorithm is used to optimize weights and thresholds of Elman neural network, and the optimized Elman neural network is used for gear box fault diagnosis. The simulation results show that the model accelerates network convergence speed and improves accuracy and precision of gear box fault diagnosis.
- gear box /
- fault diagnosis /
- Elman neural network /
- genetic algorithm