Application of Wavelet Analysis in Signal De-noising of Blast Shock Wave Overpressure

【摘要】 It’s a problem to be solved how to de-noise the signal of blast shock wave overpressure.In the conventional methods,the high frequency of the signal is cut directly by some mathematics algorithms,such as Fourier Transform,but some of the useful signal will be cut together.We adopt a new method for the signal de-noising of shock wave overpressure by wavelet analysis.There are four steps in this method.Firstly,the original signal is de-composed.Then the time-frequency features of the signal and noise are analyzed.Thirdly,the noise is separated from the signal by only cutting its frequency while the useful signal frequency is reserved as much as possible.Lastly,the useful signal with least loss of information is recovered by reconstruction process.To verify this method,a blast shock wave signal is de-noised with FFT to make a comparison.The results show that the signal de-noised by wavelet analysis approximates the ideal signal well.更多还原

【Abstract】 It’s a problem to be solved how to de-noise the signal of blast shock wave overpressure.In the conventional methods,the high frequency of the signal is cut directly by some mathematics algorithms,such as Fourier Transform,but some of the useful signal will be cut together.We adopt a new method for the signal de-noising of shock wave overpressure by wavelet analysis.There are four steps in this method.Firstly,the original signal is de-composed.Then the time-frequency features of the signal and noise are analyzed.Thirdly,the noise is separated from the signal by only cutting its frequency while the useful signal frequency is reserved as much as possible.Lastly,the useful signal with least loss of information is recovered by reconstruction process.To verify this method,a blast shock wave signal is de-noised with FFT to make a comparison.The results show that the signal de-noised by wavelet analysis approximates the ideal signal well.更多还原