摘要
现场采样获得的液压系统压力脉动信号通常含有很多的噪声,如果不能有效地消除噪声,那么故障特征参量的提取将会受到很大的影响,从而影响液压系统故障诊断的准确性。针对压力脉动信号非平稳随机性、统计特性不可预知等特点,提出一种基于小波自适应滤波的信号消噪方法,并将其应用于采集到的液压系统压力脉动信号的消噪中。通过实例分析,验证了基于小波变换的自适应滤波的信号消噪方法要优于传统的自适应滤波的信号消噪方法。
The pressure fluctuation signal of hydraulic system that is acquired at actual working spot usually includes large amount of noise.Extraction of the fault characteristic information will be influenced greatly if the pressure fluctuation is not effectively eliminated,as well the accuracy of the fault diagnostics.Aiming at the characters of non-stationary and randomness of the pressure fluctuation signal,a new method based on wavelet theory and self-adaptive filtering was presented to eliminate the pressure fluctuation.Through an actual example,it is demonstrated the de-noising effect of the self-adaptive filtering method based on wavelet theory is better than that of traditional self-adaptive filtering method.
出处
《机床与液压》
北大核心
2012年第9期151-153,157,共4页
Machine Tool & Hydraulics
关键词
小波理论
自适应滤波
消噪
液压系统
故障特征
Wavelet theory
Self-adaptive filtering
De-noising
Hydraulic system
Fault characteristic
