基于EEMD和小波阈值法的爆破振动信号预处理研究

针对爆破振动信号去噪和趋势项消除问题，借助相关性分析，引入了一种基于集合经验模态分解(EEMD)和小波阈值法的预处理滤波方法。首先运用EEMD方法进行信号分解，利用互相关系数进行含噪IMF分量和趋势项分量的预选，然后分别借助自相关函数特性和频带特点进行判断，最后完成含噪分量的小波阈值去噪和趋势项分量的去除，重构波形。实例验证结果表明，该方法能有效消除噪声、趋势项干扰，保留波形真实信息，进而提高频谱分析精度。

Pretreatment of Blasting Vibration Signal Based on EEMD and Wavelet Threshold Method

In order to solve the problems of denoising and trend component elimination for blasting vibration signals, a pretreatment of filter based on ensemble empirical mode decomposition (EEMD) and wavelet threshold method was introduced by means of correlation analysis. Firstly, the signal was decomposed with EEMD method, and pre-selection of the noisy IMF component and the trend component was performed by using the cross-correlation coefficient; secondly, the autocorrelation function characteristics and frequency band characteristics can be respectively usded for judgement; finally, the waveform was reconstructed after the noisy component of wavelet threshold was denoised and trend component was removed. The practical verification results show that this method can effectively eliminate the interference by noise and trend component, retain the true information of waveform, thus improving the accuracy of spectrum analysis.