基于最优小波基选取的遥测振动信号降噪方法

A Denoising Method for Telemetry Vibration Signal Based on the Seletion of Optimal Wavelet Basis Function

针对飞行器试验遥测振动信号频率内容丰富,小波降噪最优小波基函数难以选取问题,提出了一种结合EMD的最优小波基选取方法。利用EMD将振动信号分解为一系列IMF分量,利用互相关系数和自相关函数判断含噪分量,并以含噪分量离散小波变换系数的香农熵为依据选择最优小波基,以最优小波基分别对含噪IMF分量进行降噪处理,将降噪后IMF分量与其余IMF分量累加获得降噪后信号。仿真和试验数据处理结果证明,基于最优小波基选取的降噪方法与小波降噪、EMD降噪相比,信噪比得到了有效提升,在遥测振动信号预处理中具有实际应用价值。

In response to the problem of the rich frequency content of telemetry vibration signals in aircraft testing and the dif-ficulty in selecting the optimal wavelet basis function for wavelet denoising,this article proposes an optimal wavelet basis selection method combined with EMD.The article uses EMD to decompose vibration signals into a series of IMF components,uses cross-cor-relation coefficients and autocorrelation functions to determine the noisy components,and selects the optimal wavelet basis based on the Shannon entropy of the discrete wavelet transform coefficients of the noisy components.The optimal wavelet basis is used to de-noise the noisy IMF components separately,and the denoised IMF components are accumulated with the other IMF components to obtain the denoised signal.The simulation and experimental data processing results demonstrate that the denoising method based on optimal wavelet basis selection has effectively improved the signal-to-noise ratio compared to wavelet denoising and EMD denois-ing,and has practical application value in the preprocessing of telemetry vibration signals.