摘要
在机械多源振动传播和卷积混合模型的基础上,提出一种基于时域的多振源卷积混合信号的盲源分离算法。该算法以独立性为评判准则,采用反向学习和合理简化滤波器系数的方式,进行滤波器系数的学习,进而实现基于时域的多振源卷积混合信号的分离。仿真试验和多机振动源试验结果表明,该算法对于多源卷积混合信号具有很好的分离效果,可应用于机械设备多激振源卷积混合情况下机械振动源信号的有效分离。
On the basis of the model of multi-source mechanical vibration propagation and convolution mixtures, a blind source separation （BSS） algorithm for convolution mixture signals with multiple vibration sources based on time domain is proposed. This algorithm takes independence as judgment criterion, and carries out the learning of filter coefficient by adopting the mode of back- ward learning and rational simplification of filter coefficient, then realizes the separation of convolution mixture signals with multi- ple vibration sources based on time domain. The results of simulation test and multi-source mechanical vibration test indicate that the algorithm can achieve good effect in separating multi-source convolution mixture signals.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2009年第1期189-194,199,共7页
Journal of Mechanical Engineering
基金
国家自然科学基金资助项目(50205025
50675194)。
关键词
机械振动
卷积混合
多振源
盲源分离
时域
Mechanical vibration Convolutive mixture Multi vibration sources Blind source separation Time domain
