| Before the advent of Wavelet Analysis, the chief tool on signal processing is Fourier analysis. Fourier analysis is an irreplaceable tool on processing stationary stochastic signals, but is at a loss on processing non-stationary time-varying signals that abound in real world. Thus wavelet analysis was introduced. It is development of methods on signal processing. Wavelet analysis is an effective method for processing an unsteady signal. It is a useful tool for time-frequency analysis, and is therefore applied in various fields. During many years theoretical and applied study, it is superior to other tools on processing time-varying signals.The samples used in this study were medium density fiberboard (MDF). Their dynamic modulus of elasticity was measured by flexural vibration and longitudinal resonant vibration .A comparison is made between FFT Analysis and wavelet Analysis.The main results are as follows:1) We can measure the dynamic elasticity modulus of MDF by Wavelet Analysis.2) The modulus of elasticity that measured by different tests was different. But there was a correlation between them.3) The research on the application of wavelet transform in signal noise reduction is conducted. The approach of noise reduction based on wavelet denoise is proposed. The results of experiments with vibration signal of the samples show that the approach can be applied to noise reduction effectively.4) The research on the application of wavelet transform in non-stationary signal is conducted. It is made out that wavelet analysis in these signals has a great advantage over Fourier analysis. Through processing vibration signal of the samples, it can be seen that the different defects of MDF have the different influences to the vibration character of the samples.5) It can be acquired that wavelet analysis has the advantages in collecting the defect characters of the MDF. In conclusion, wavelet analysis is worthwhile doing both in theory and practices.
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