滚动轴承含噪声谐波信号的欠确定盲源分离方法研究

目前使用的大多数盲源分离方法都依赖于观测传感器数量大于或等于信号源数目这样一个基本假设。算法主要针对传感器数量m小于源信号数量n(欠确定)情况下旋转机械含噪声谐波信号的盲源分离问题展开研究。它在输入信号频域稀疏性假设和源信号之间线性混合假设的前提下,提出了一种势函数聚类的源数目估计方法,并对通道衰减和延时进行了计算。实验信号仿真结果证明了该方法的可行性和可靠性。

Underdetermined Blind Source Separation of Noisy Harmonic Signals for Rolling Element Bearing Diagnosis

Most of the blind source separation methods were dependent on the fact that the observing sensors are more than or equal to the number of signal source.The algorithm in this paper is aimed to research into the blind source separation of noisy harmonic signals from rotating machine when the underlying system is underdetermined,that is,the cases in which the separation of n sources is made from m mixtures while m is smaller than n.Based on the assumption that the input distribution is sparse and the mixture procedure is instantaneous,a potential-function clustering method for estimating the number of information sources was proposed and a calculation on the attenuation matrix and the delay matrix were made.Signal simulation in experiment shows the applicability and reliability of the method under discussion.