摘要
介绍了一种采用主减速器总成跑合试验的振动信号进行准双曲面齿轮主减速器质量评价的方法。利用时、频域分析和小波包分解对能反映故障特征的参数进行提取;利用MATLAB神经网络工具箱对BP神经网络进行训练并实现故障模式的识别。通过实测信号的试验结果表明,该方法能对准双曲面齿轮主减速器的质量进行有效的评价。
The quality assessment method of hypoid gear main reducer for main reducer assembly running experiment vibration signals is presented.The parameters reflecting the failure characteristic of gears are extracted by using time-frequency domain analysis and wavelet packet analysis.The nerve network toolbox of MATLAB is used to train the program of BP nerve network,and the fault identification is carried out.The results show that the quality assessment method to hypoid gear main reducer is effective.
出处
《机械传动》
CSCD
北大核心
2010年第10期73-77,共5页
Journal of Mechanical Transmission
