DSQ水管倾斜仪信号随机噪声压制研究

Research on Random Noise Suppression of DSQ Water-Tube Tiltmeter Signal

基于自适应噪声完备集合经验模态分解CEEMDAN和小波去噪,提出一种DSQ水管倾斜仪信号随机噪声压制方法。首先将信号进行CEEMDAN分解,得到若干个本征模态函数IMF,分解数量随不同信号噪声动态变化;然后计算每条IMF和原信号的相关性系数,对处于系数阈值范围内的IMF作小波变换处理;最后执行线性重构,得到去噪后的信号。仿真和实际去噪实验结果表明,随机噪声压制效果明显,信号有效成分保留比率较高,优于其他同类方法。

Applying adaptive noise-complete ensemble empirical modal decomposition(CEEMDAN)and wavelet denoising,we propose a random noise suppression method for DSQ water pipe tiltmeter signals.Firstly,the signals are decomposed by CEEMDAN to obtain several eigen mode functions(IMFs),and the number of decompositions varies dynamically with different signal noises.Then we calculate the correlation coefficient values of each IMF and the original signal,and calculate the original signal.By wavelet transform we process the IMFs within the threshold of the coefficient value.Finally,we perform the linear reconstruction to obtain the denoised signal.The simulation and actual denoising experimental results show that the random noise suppression effect of this method is obvious,and the retention ratio of the effective components of the signal is higher and better than other similar methods.