Shear probe works under a tough environment where the turbulence signals to be measured are very weak. The measured turbulence signals often contain a large amount of noise. Due to wide frequency band, noise signals c...Shear probe works under a tough environment where the turbulence signals to be measured are very weak. The measured turbulence signals often contain a large amount of noise. Due to wide frequency band, noise signals cannot be effectively removed by traditional methods based on Fourier transform. In this paper, a wavelet thresholding denoising method is proposed for turbulence signal processing in that wavelet analysis can be used for multi-resolution analysis and can extract local characteristics of the signals in both time and frequency domains. Turbulence signal denoising process is modeled based on the wavelet theory and characteristics of the turbulence signal. The threshold and decomposition level, as well as the procedure of the turbulence signal denoising, are determined using the wavelet thresholding method. The proposed wavelet thresholding method was validated by turbulence signal denoising of the Western Pacific Ocean trial data. The results show that the propsed method can reduce the noise in the measured signals by shear probes, and the frequency spectrums of the denoised signal correspond well to the Nasmyth spectrum.展开更多
In process of seismic exploration,the noise of seismic signals produces serious interference. Conventional methods of wavelet threshold denoising cannot fully use the characteristics of seismic signals due to its limi...In process of seismic exploration,the noise of seismic signals produces serious interference. Conventional methods of wavelet threshold denoising cannot fully use the characteristics of seismic signals due to its limitations. There is always a certain degree of deviation between estimated value and actual value. In this study,a method of seismic data denoising is proposed,the authors use the current coefficients,the parent coefficients and the neighborhood coefficients based on dual-tree complex wavelet transform( DTCWT) and related sub-band denoising model( TrivaS hrink) to achieve the optimal estimation of shrinking factor and get the noise reduction of seismic records. It is found that the method is better than conventional methods of wavelet threshold denoising in removing random noise.展开更多
基金Supported by National Natural Science Foundation of China (No. 50835006 and No. 51005161)National High-Tech R&D Program ("863"Program) of China (No. 2010AA09Z102)
文摘Shear probe works under a tough environment where the turbulence signals to be measured are very weak. The measured turbulence signals often contain a large amount of noise. Due to wide frequency band, noise signals cannot be effectively removed by traditional methods based on Fourier transform. In this paper, a wavelet thresholding denoising method is proposed for turbulence signal processing in that wavelet analysis can be used for multi-resolution analysis and can extract local characteristics of the signals in both time and frequency domains. Turbulence signal denoising process is modeled based on the wavelet theory and characteristics of the turbulence signal. The threshold and decomposition level, as well as the procedure of the turbulence signal denoising, are determined using the wavelet thresholding method. The proposed wavelet thresholding method was validated by turbulence signal denoising of the Western Pacific Ocean trial data. The results show that the propsed method can reduce the noise in the measured signals by shear probes, and the frequency spectrums of the denoised signal correspond well to the Nasmyth spectrum.
基金Supported by the National "863" Project(No.2014AA06A605)
文摘In process of seismic exploration,the noise of seismic signals produces serious interference. Conventional methods of wavelet threshold denoising cannot fully use the characteristics of seismic signals due to its limitations. There is always a certain degree of deviation between estimated value and actual value. In this study,a method of seismic data denoising is proposed,the authors use the current coefficients,the parent coefficients and the neighborhood coefficients based on dual-tree complex wavelet transform( DTCWT) and related sub-band denoising model( TrivaS hrink) to achieve the optimal estimation of shrinking factor and get the noise reduction of seismic records. It is found that the method is better than conventional methods of wavelet threshold denoising in removing random noise.
