变分模态分解和熵理论在超声信号降噪中的应用

Application of variational mode decomposition and entropy theoryin ultrasonic signal de-noising

针对超声检测信号中结构噪声难以去除的问题,提出了一种变分模态分解(Variational Mode Decomposition,VMD)和小波能量熵阈值(Wavelet Energy Entropy Threshold,WEET)联合降噪的算法.分析了含噪系统熵增的特性以及结构噪声在不同时间段的分布特征,提出了用小波能量熵表征信号的含噪状态,并以小波能量熵最大子区间的小波系数参与计算各个尺度层的阈值.对仿真及实测信号进行处理,结果表明,该方法(VMD-WEET)能很好地抑制超声回波信号中存在的白噪声及结构噪声,还原了准确的波形特征,验证了其有效性.

Aiming at the problem of difficult to remove the structural noise in ultrasonic testing signals,this paper presented a de-noising method which combined variational mode decomposition（VMD）and wavelet energy entropy threshold（WEET）.Firstly,the characteristic of entropy increase in noisy system and the distribution feature of structural noise in different period were analyzed.Then,the state of signal with noise was characterized by wavelet energy entropy and the threshold of wavelet decomposed in different scales ware determined according to the wavelet energy entropy.Simulation and experimental results show that the de-noising method（VMD-WEET）in this paper can restrain the noise and restore the accurate waveform to verify its effectiveness.