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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。
Comparisons were made between TVAR, STFT, WVD, Choi-Williams distribution (CWD), continuous wavelet transform (CWT) and Hilbert-Huang transform HHT) and other time-frequency analysis of time-frequency focusing, resolution, cross-interference suppression and computational efficiency. The analysis of the vibration simulation signal of the rotor starting process with FM and amplitude modulation shows that the TVAR has better overall performance for such signals. Based on the analysis results of STFT and the TVAR method, The vibration signal of the experimental rotor was analyzed. The results show that TVAR not only can effectively analyze the non-stationary vibration signal during rotor starting, but also has strong signal feature extraction and anti-noise ability.