结合EMD和LSF的振动信号降噪方法的研究

Noise Reduction Method of Vibration Signal Combining EMD and LSF

针对原始振动加速度信号中存在的低频趋势项信号在通过数学积分变换时存在严重失真的问题,提出了采用最小二乘法(least squares fit,简称LSF)和经验模态分解(empirical mode decomposition,简称EMD)相结合的方法,实现过滤原始信号中干扰信号的目的。该方法通过对经验模态分解得到的固有模态函数(intrinsic mode function,简称IMF)去除趋势项后进行重构以达到信号降噪的目的。采用该方法分别对模拟信号和某型号干式真空泵的振动实测数据进行了降噪处理,再进行信号积分变换,通过对比证明了该方法能够弥补单一方法在处理信号低频趋势项时的不足,提高了振动信号分析的可靠性。

In view of the serious distortion of the low frequency trend term signal in the original vibration acceleration signal when it is transformed by mathematical integration,a method combining least squares fit(LSF)and empirical mode decomposition(EMD)is proposed to filter the interference signal in the original signal. In this method,the intrinsic mode function(IMF)obtained from empirical mode decomposition is reconstructed after removing the trend term to achieve the purpose of signal noise reduction. The method is used to reduce the noise of the analog signal and the vibration data of a certain type of dry vacuum pump,and then the signal integral transformation is carried out. The comparison shows that this method can make up for the deficiency of single method in processing low frequency trend term of signal. It improves the reliability of vibration signal analysis and provides a good foundation for further research on fault monitoring and diagnosis of dry vacuum pump.