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The vibration signal is one of the significant signals that reflects the fault. In allusion to the shortcomings of traditional signal analysis method in the high-frequency and nonstationary signal analysis, the wavelet theory and approximate entropy algorithm are introduced into the signal analysis in order to propose a new vibration signal analysis (WTAEAVSA) method in this paper. In the proposed WTAEAVSA method, the wavelet transform technology is used to reduce the noise and decompose the low and high frequency vibration signal in order to obtain the signal characteristics of different frequency bands. Then the approximate entropy algorithm is used to determine the complexity and irregular degree of vibration signal in the different scale and different frequency band, so as the non-stationary characteristics of vibration signal are extracted. At last, some simulated signals with time-domain and frequency-domain from the normal signal are used to test the characteristics of the proposed WTAEAVSA method. The simulation results show that the proposed WTAEAVSA method can extract the characteristic vector from vibration signal, visually and sharply reflect the changes of the mechanical states.

Research on a Signal Analysis Method based on Wavelet Theory and Approximate Entropy Algorithm