摘要
针对轴承故障信号的降噪处理,研究了粒子滤波方法和它在信号降噪中的应用。首先建立轴承故障振动信号的数学模型,将其作为粒子滤波的状态方程;然后提取背景噪声,将其和状态信号一起作为观测信号,得到观测方程,据此对原始真实信号进行估计,得到降噪后的信号,并通过仿真分析可知降噪前后的信噪比有明显的提高;最后将粒子滤波降噪思想用于所采集的实验室传动箱轴承故障振动信号的降噪处理,获得了较好的噪降效果。
Aimed at bearing fault signal noise reduction processing,this paper studies the particle filter method and its application in signal noise reduction.Firstly,the mathematical model for bearing fault vibration signals is established and it is considered as the state equation of the particle filter.Then, extracting the background noise,the noise signal with the state signal as an observation signal,an observation equation is obtained.The original real signal is estimated,and the obtained estimate signal is the de-noising signal.Through the simulation analysis,the signal-to-noise ratio is improved before and after noise reduction.Finally,the particle filter for the noise reduction is used for bearing fault vibration signal noise reduction processing in laboratory transmission boxes,thus obtaining same good effect of the noise reduction.
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2011年第3期354-356,398-399,共3页
Journal of Vibration,Measurement & Diagnosis
基金
国家自然科学基金资助项目(编号:50875247)
山西省自然科学基金资助项目(编号:2007011070)
关键词
轴承故障
粒子滤波
振动信号
降噪
bearing faults particle filter vibration signal noise reduction
