相关机械振源的盲源分离方法

Blind source separation of statistically correlated sources

相关源不满足独立分量分析关于源的统计独立性假设,标准的独立分量分析方法无法准确分离相关机械振源信号。在相关振源信号的部分频带满足统计独立的假设前提下,提出了一种基于小波包分解的相关机械源盲源分离方法。该方法将观测信号用小波包分解成子带观测信号,根据互信息标准选择相关性较小的若干子带观测信号重构观测信号。通过重构的观测信号的独立分量分析估计分离矩阵,然后用该矩阵分离原始观测信号从而实现相关机械振源信号的分离。仿真试验验证了该方法的有效性。

Standard independent component analysis is unable to separate statistically correlated machine vibration sources because the assumption of statistical independence is no more satisfied. Assuming some sub-components of correlated machine vibration sources are independent, a novel blind source separation method for correlated vibration sources seperation based on wavelet packet decompostion was proposed. In the method, subband observed signals were obtained by decomposing orignal observed signals with wavelet packet transform, the new observed signals were reconstructed by some subband observed signals with less correlation according to the mutual information creterion, the separation matrix was estimated through the reconstructed observed then, the correlated machine vibration sources were separated in Simulations testify the validity of the proposed method. signals by using independent component analysis; agreement with the estimated separation matrix.