变工况下转子振动信号的时频分析方法比较

Comparison on Time-frequency Analysis Methods for Nonstationary Rotor Vibration Signal Processing

比较了时变参数自回归模型(TVAR)、短时傅里叶变换(STFT)、Wigner-Ville分布(WVD)、Choi-Williams分布(CWD)、连续小波变换(CWT)以及Hilbert-Huang变换(HHT)等几种时频分析方法的时频聚焦性、分辨率、交叉干扰项抑制以及计算效率。对一个具有调频和调幅特性的转子启动过程振动仿真信号进行分析,得出针对此类信号TVAR具有较好综合性能;以STFT的分析结果为比较基准,利用TVAR方法对加速启动工况下采集的实验台转子振动信号进行了分析。结果表明:TVAR不仅能够有效地分析转子启动过程非平稳振动信号,而且具有较强的信号特征提取和抗噪声能力。

Several time- frequency representations including time varying autoregressive model （TVAR）,short time Fourier transform （STFT）, Wigner - Ville distribution （WVD）, Choi - Williams distribution （CWD）, continuous wavelet transform （CWT） and Hilbert- Huang transform （HHT）were compared to the respect of their achievable time and frequency resolution, cross-term suppression and computational load. Those methods were taken to analyze an AM - FM signal simulating the vibration of a running-up rotor. Comparing the results, it could be concluded that TVAR with the best comprehensive performance to such kind of signal. Consequently, TVAR was applied to process a real running-up vibration signal of a rotor with STFT as a benchmark. The result showes TVAR has potential to process nonstationary signals with superior feature extraction ability, and is fairly noise insensitive. In conclusion, TVAR provides a superior approach for time - frequency analysis and fault diagnosis of rotation machine under nonstationary conditions.