基于自适应和小波模极大值重构的地面核磁共振信号噪声压制方法

Noise cancellation algorithm for surface magnetic resonance signals based on self-adaption and reconstruction of wavelet modulus maximum value

针对核磁共振信号中的噪声,在二进小波变换基本原理的基础上,研究了小波模极大值重构方法,将该方法与自适应滤波方法相结合应用到含噪声信号的干扰滤除中,通过分析包络信号拟合后的初始振幅、平均衰减时间和相位等数据可知,含噪声信号经自适应和小波模极大值重构方法滤波处理后拟合得到的特征参数误差最小且信噪比得到最大的提高。同时,通过实测数据得知采用自适应和小波模极大值重构方法进行噪声滤波后的结果与钻孔结果的一致性较好,验证了本文所提方法的有效性。

Based on the principle of binary wavelet transform,a method of reconstruction of wavelet modulus maximum value for the noise in Magnetic Resonance Sound（MRS）signals is proposed.Combined with adaptive notch filter,the method is used to filter out noise.By analysis of the data of the initial amplitude,the average decay time and phase etc posterior the fitting of envelope signals,it is known that after several times of filtering processing of the noise signals,the obtained fitting error of the characteristic parameters is minimum,and the Signal to Noise Ratio（SNR）is obviously improved.Real data were measured and noise filtering was carried out using the proposed method in this paper.The obtained results are in good agreement with the drilling results,which verifies the effectiveness of the proposed method.