基于系统模型的齿轮箱故障诊断

Gear Box Fault Diagnosis Based on System Model

用时间序列和神经网络相结合的方法,建立振动信号的时间序列模型,作为齿轮箱系统模型。分析模型特性,提取齿轮箱故障的特征参数,然后以此建立相应的神经网络,识别齿轮箱的运行故障。结果表明该方法能很大地提高诊断的准确性。

Based on the integration of time series and neural network methods,the vibration signal time series model is set up,which is taken as gear box system model.The model characteristic is analyzed,the characteristic parameters of the gear box fault are extracted,and the corresponding neural network is constructed,to identify the gearbox fault.The results show the method can greatly improve the accuracy of diagnosis.