Time-Frequency Analysis of Noisy Vibration Signal Based on Improved Hilbert-Huang Transform

Abstract

Aimed at the phenomenon of modal confusion and lack of practical significance of instantaneous frequency caused by Hilbert-Huang transform (HHT) noisy vibration signal time-frequency analysis, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is obtained by improving empirical mode decomposition (EMD), and in combination with multiscale permutation entropy (MPE) to suppress EMD modal confusion. At the same time, improved normalized Hilbert transform(INHT) is obtained by improving Hilbert transform, and finally the CEEMDAN·MPE-INHT time-frequency analysis algorithm is formed. In order to verify the accuracy of time-frequency analysis of CEEMDAN·MPE-INHT noisy vibration signals, a comparative study of time-frequency analysis of EMD-HT, EEMD-NHT, CEEMDAN-INHT and CEEMDAN·MPE-INHT noisy simulation vibration signals is conducted. The results show that CEEMDAN can control low frequency noise; MPE can suppress high frequency noise; INHT can make Hilbert transform not constrained by Bedrosian theorem. Finally, CEEMDAN·MPE-INHT algorithm is applied to the time-frequency analysis of noisy vibration signals in practical engineering. The time spectrum of intrinsic mode function (IMF) decomposed by CEEMDAN·MPE after INHT processing has a high resolution in time domain and frequency domain, which can improve the extraction accuracy of time-frequency characteristic parameters and help control the harm of vibration signals.

Keywords

• empirical mode decomposition
• hilbert transform
• modal confusion
• intrinsic mode function