基于WOA-VMD-MPE算法的矿山爆破振动信号 降噪研究及应用.

The blasting vibration signal in the mine environment contains a lot of high frequency noise, which seriously affects the authenticity of the blasting vibration signals In this paper, targeting the phenomenon that there is a lot of high frequency noise in the blast signals, using blast vibration data from an open pit mine in Yunnan as a research object, this paper proposes research on noise reduction of blast vibration signals based on adaptive WOA VMD MPE blast vibration signal denoising method. WOA optimization algorithms are used to process blast vibration signals from three mines, and the optimal parameter combination of the VMD algorithm K、q is found, which is broken down via the VMD algorithm, and the IMF components with MPE above 0. 6 are removed in order to obtain the effect of the noise reduction. The results show that it can be seen that the signal to noise ratio of the vibration waveforms optimized by the WOA VMD algorithm is the highest, which is 15. 23,25. 51, 27. 2 respectively, and the mean squared error is the lowest, which is 8. 51, 8. 73,5. 91, respectively. Compared to the EEMD and CEEMD algorithms, the signal to noise ratio of the WOA VMD algorithm is increased by 56% and 44%, and the mean squared error is decreased by 46 % and 42 %, respectively. It has a better noise reduction effect than the EEMD and CEEMD algorithms. It can better remove high frequency noise and retain the original vibration waveform information from the blast, thus verifying the universality of the algorithm. [ABSTRACT FROM AUTHOR]