Noise Reduction Method of Open-pit Blasting Vibration Signal Based on PEMD-MPE Algorithm
In order to remove the noise components mixed in the blasting vibration signals of open-pit mine,a noise reduction method based on the PEMD-MPE algorithm was proposed.This algorithm obtains a completely orthogonal Intrinsic Mode Function(IMF)components through Adaptive Orthogonal Empirical Mode Decomposition(PEMD).Subsequently,it performs a randomness test on the IMF components and calculates its Mean Power Entropy(MPE).Finally,based on a preset entropy threshold of 0.6,it determines whether a component is noise.If the obtained MPE is greater than 0.6,the component is identified as a noise component and needs to be removed,thus achieving the purpose of noise recluction.Applying this algorithm to denoise measured open-pit mining explosion vibration signals,the results indicate that compared to the EMD-MPE and EEMD-MPE algorithms,the proposed algorithm improves the signal-to-noise ratio by 3.520 dB and 1.107 dB,respectively.It exhibits the best denoising effect,with the smallest reconstruction standard deviation and root mean square error,providing better fidelity to the original signal.Using Adaptive Optimal Kernel(AOK)time-frequency analysis technology to analyze the signal waveforms before and after denoising,a comparison reveals consistent main frequencies.Throughout the denoising process,peak energy and energy in the main frequency band(0～300 Hz)do not show a significant decrease.This indicates that the PEMD-MPE algorithm,while preserving the authenticity of the real signal,more effectively removes noise components.
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