Q estimation based on crosscorrelation function and S transform in ultrasonic

Abstract

A novel method for Q (quality factor Q) estimation is proposed based on crosscorrelation function and S-transform (CRST). We use the S-transform to analyse the time–frequency spectra of the crosscorrelation coefficients and extract the amplitude spectra corresponding to the maximum energy time in time–frequency spectra. The Q can be estimated using the spectra ratio based on the linear relationship between spectral ratio and frequency. Meanwhile, two time window factors are added to the Gaussian window function in S-transform to make the S-transform applicable for Q estimation. Firstly, through numerical tests and standard sample experiments, the feasibility and noise immunity of the CRST method are studied. Secondly, the applicability and stability of this method are studied using artificial samples with different Q. Finally, the stability and accuracy of the CRST method are analysed by comparing with the conventional spectrum ratio method (SR) through rock samples. The experimental results show that the Q of samples can be obtained by using the time–frequency spectrum information of the crosscorrelation coefficient. The proposed time window factors can effectively eliminate the errors caused by the conventional Gaussian window function, which the relative errors can reach about 40%. The CRST can reduce the effect of the frequency bandwidth for regression analysis. The new method can ensure that the maximum error of different Q factors (Q > 15) is about 5%. Compared with the conventional spectrum ratio method, the CRST method not only has better noise immunity, but also has higher stability and accuracy.