联合SSA-VMD与改进小波阈值的发电机振动信号降噪方法

Generator vibration signal denoising method based on improved wavelet threshold of SSA-VMD

经传统小波阈值函数降噪后的信号与原始信号相比,存在一定恒定误差。利用变分模态分解(variational mode decomposition, VMD)处理信号时,不同惩罚因子α及模态分解层数K取值极大影响降噪效果。为此,将联合麻雀搜索算法(sparrow search algorithm, SSA)-VMD与改进小波阈值降噪法引入发电机振动信号处理。先利用SSA以最小包络熵为目标函数优化VMD分解参数α与K,获取最优降噪效果;再将含噪振动信号经VMD解构为K个本征模态函数(intrinsic mode functions, IMF),利用改进小波阈值对低于所设置IMF阈值的分量再次降噪;最后,将降噪后的IMF分量重组获得最终降噪信号。通过Matlab验证分析可知,联合SSA-VMD与改进小波阈值降噪法能有效降低信号均方误差、显著提升发电机振动信号的降噪效果。

There are some constant errors between the original signals and the denoised signals filtered by the traditional wavelet threshold function.The variational mode decomposition(VMD)sets different penalty factorsαand different numbers of modal decomposition layers K in signal processing,affecting the noise reduction enormously.Therefore,this paper introduces the improved wavelet threshold denoising method and sparrow search algorithm-variational mode decomposition(SSA-VMD)into generator vibration signal processing.First,SSA is employed to optimize the VMD decomposition parametersαand K with the minimum envelope entropy as the objective function to achieve the optimal noise reduction.Then,the noisy vibration signal is decomposed into K intrinsic mode functions(IMF)by VMD,and the improved wavelet threshold is employed to denoise again the components below the set IMF threshold.Finally,the denoised IMF is recombined to obtain the ultimate noise reduction signal.An analysis through Matlab shows the improved wavelet threshold function denoising method together with SSA-VMD effectively reduces the mean square error of the signals and markedly improves the denoising of generators’vibration signals.