针对储油罐罐底腐蚀声发射信号易受多种噪声干扰，影响定位精度和评判准确性的问题，在对干扰噪声进行分析的基础上，提出了一种基于独立分量分析的信号去噪方法。首先利用混合因子分析进行预处理，再利用改进的独立分量分析算法实现源信号的分离，根据时域和频域的相关知识，将独立分量中的噪声通道去除，从而达到声发射信号有效去噪的目的。试验表明，独立分量分析较常用的去噪方法能得到更高的信噪比，去噪后的信号定位精度更高，从而证明该预处理方法和改进的独立分量分析算法的有效性。

Following the analysis of the interference noise, a method based on Independent Component Analysis ( ICA ) to denoise the acoustic emission signals is presented to overcome the disadvantage of AE signals being strongly affected by the background noises, which shall affect the accuracy of positioning and judgment. Firstly, the signals are pretreated by the mixing factor analysis method, then, the observed signals are decomposed of several independent components by the improved independent component analysis algorithm. By setting the noise component to be zero according to some priori knowledge in time domain or frequency domain of the signals, the purposes of noise elimination could be achieved. Experimental results show that the independent component analysis can get a higher SNR and positioning accuracy than commonly de-noising method. It thus proves that the pretreatment methods and improved independent component analysis algorithm described in the text are effective.