摘要
利用旋转机械的振动信号的循环平稳特性,采用基于二阶统计量(Second O rder Statistic,SOS)的盲均衡技术从多个传感器信号中恢复出"真实的"振动源信号,实现了同类信号的数据级融合。以滚动轴承故障信号的阶次谱结构为先验知识,提出了用于滤波性能评价的两个指标,实现了盲均衡滤波器参数的优化,从而给出了一种可用于滚动轴承故障诊断的半盲信号处理方法。采用某型单级减速齿轮箱的实验数据验证了该方法的有效性。
In accordance with the cyclostationary nature of the vibration signal of rotating machine,the blind equalization technique based on output second order statistic(SOS) was introduced to recover 'real' vibration signal from multi-sensors signals,which is essentially the data level information fusion for homogeneous sensors signals.Based on the prior knowledge of the order spectral structure of the faulty vibration signal of rolling bearing,two performance indexes were proposed to optimize the blind equalization filter parameters.Finally,a semi-blind signal processing method for rolling bearing fault diagnosis was given.The performance of the method was verified with experiment data on a single reduction gearbox test rig.
出处
《振动与冲击》
EI
CSCD
北大核心
2009年第12期80-83,共4页
Journal of Vibration and Shock
基金
国家自然科学基金资助项目(50375157
50775219)
关键词
半盲信号处理
多传感器
数据级融合
滚动轴承
故障诊断
semi-blind signal processing
multisensors
data level information fusion
rolling element bearing
fault diagnosis
