基于改进变分模态分解的液体密度测量中超声回波去噪方法

摘要：

超声波液体密度测量回波中包含大量噪声， 难以准确获取有效回波波形， 导致密度测量精度不高。 为此， 提出了一种基于改进后变分模态分解（Variational mode decomposition,VMD）的回波信号去噪方法。 由于传统VMD方法中分解层数难以确定， 因此构造了中心频率相似因子作为判断准则来自适应选定VMD分解层数。 首先， 通过首次分解后的中心频率计算出相似因子， 并根据相似因子选定VMD分解层数； 其次， 利用VMD算法将回波信号分解成若干个具有单一成分的模态分量， 利用超声发射信号特点提取出有效回波成分； 最后， 通过分离所得的有效回波信号， 提取回波波形及时间， 由此计算出液体密度。 实验结果表明， 利用改进的VMD算法分解回波信号可以将有效回波信号的信噪比提高至20.64 dB， 并准确获得时间、 幅值等回波信号基本信息。 与集合经验模态分解(Ensemble empirical mode decomposition， EEMD)相比， 该方法可以有效地抑制模态混叠， 并最大限度地保留信号的细节特征， 提高液体密度测量的精度， 密度测量精度可达满量程的0.21%。

 The ultrasonic echo in liquid density measurement often suffers noise, which makes it difficult to obtain the useful echo waveform, resulting in low accuracy of density measurement. A denoising method based on improved variational mode decomposition (VMD) for noise echo signals is proposed. The number of decomposition layers of the traditional VMD is hard to determine, therefore, the center frequency similarity factor is firstly constructed and used as the judgment criterion to select the number of VMD decomposition layers adaptively; Secondly, VMD algorithm is used to decompose the echo signal into several modal components with a single modal component, and the useful echo components are extracted based on the features of the ultrasonic emission signal; Finally, the liquid density is calculated by extracting the amplitude and time of the echo from the modal components. The simulation results show that using the improved VMD to decompose the echo signal not only can improve the signal-to-noise ratio of the echo signal to 20.64 dB, but also can accurately obtain the echo information such as time and amplitude. Compared with the ensemble empirical mode decomposition (EEMD), this method effectively suppresses the modal aliasing, keeps the details of the signal to the maximum extent while suppressing noise, and improves the accuracy of the liquid density measurement. The density measurement accuracy can reach 0.21% of full scale.