摘要
传统的信号处理方法不易提取故障特征,给齿轮箱的故障诊断带来很大困难。建立了齿轮箱故障诊断的灰色神经网络模型,结果验证该模型的诊断结果具有较高准确性,适于提取故障信号的非线性特征,理论上为齿轮箱故障诊断提供了一个快速有效的方法。
The traditional signal processing method is difficult to extract the fault features,and the great difficulty is brought to gearbox fault diagnosis.The gray neural network model is established for fault diagnosis of gearbox,the results validating the diagnostic results model with high accuracy,and the nonlinear characteristic of fault signal is suit to extract.A fast and efficient way to gearbox fault diagnosis is provided in theory.
出处
《机械传动》
CSCD
北大核心
2010年第10期71-72,77,共3页
Journal of Mechanical Transmission
