基于TVAR的非平稳工况转子故障诊断技术研究

TVAR Based Fault Diagnosis for Rotation Machine under Nonstationary Conditon

分析比较了基于时变参数自回归模型(TVAR)时频分析方法与基于非参数模型的典型传统时频分析方法———STFT、CWD对非平稳信号进行分析时的时频性能和特点,TVAR方法得出的时频图具有分辨率高、无交叉干扰项以及计算速度快等优点.基于TVAR分析了从转子实验台上采集的加速过程无故障及故障状态下的振动信号,分析结果有效地揭示了变速非平稳过程转子振动信号的特性和故障特征.仿真和实验都证明TVAR非常适用于旋转机械非平稳振动信号分析.

The time-frequency analysis ability for non-stationary signals was compared between parametric model based Time-Varying Autoregressive model(TVAR) and non-parametric time-frequency methods such as the SFTF and the CWD.The three methods had been evaluated with respect to a set of simulated signals and the signals collected form a rotation machine test rig during the speed-up process.The performances of TVAR in both the time-frequency resolution and the suppression of cross term are all excellent.TVAR is suitable for non-stationary signals analysis of rotation machine.And the results effectively discover the characteristics and fault features of signals.TVAR is effective to fault diagnosis of rotation machine under nonstaionary conditions.