Mechanical Engineering Department, North China Electric Power University, Baoding 071003, Hebei Province, China

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Abstract—Vibration problems in rotors can be extremely frustrating and may lead to greatly reduced reliability. By utilizing the proper data collection and analysis techniques, the faults because of vibration can be discovered and predicted. The signal analysis is important in extracting fault characteristics in fault diagnosis of machinery. The traditional signal analysis can not settle for non-stationary vibration signal whose statistic properties are variant. To deal with non-stationary signal, time-frequency analysis techniques are widely used. The experiment data of oil whip vibration fault signal were analyzed by different methods, such as short time Fourier transform (STFT), Wigner-Ville distribution (WVD), Wavelet transform (WT) and Hilbert- Huang Transform (HHT). The experiment data of rubbing vibration faults signal were also analyzed by the HHT. Compared with these methods, it is demonstrated that the time-frequency resolutions of STFT and WVD were inconsistent, which were easy to cross or make signal lower. WT had distinct time-frequency distribution, but it brought redundant component. HHT time-frequency analysis can detect components of low energy, and displayed true and distinct time-frequency distribution. Therefore, HHT is a very effective tool to diagnose the faults of rotating machinery.

Index Terms—signal analysis, time-frequency analysis, vibration, Hilbert-Huang transform (HHT), fault diagnosis.

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Cite:Ling Xiang and Aijun Hu, "Comparison of Methods for Different Timefrequency Analysis of Vibration Signal," Journal of Software vol. 7, no.1, pp. 68-74, 2012.