Research On De-noising Method Of Micro-seismic Signal

The occurrence of coal mine power disasters will cause the underground rock to rupture,and the sensor receives the micro-seismic signals induced when the rock breaks,forming micro-seismic data.In the data acquisition process,due to the interference of noise,the collected signal contains a large number of invalid signals.At present,there are many methods for noise reduction of micro-seismic signals.Empirical mode decomposition(EMD)is a commonly used noise reduction method in the field of micro-seismic signal processing.However,the EMD algorithm has modal aliasing phenomenon,and the VMD algorithm overcomes the shortcomings of the EMD algorithm.However,since the VMD algorithm cannot completely separate the signal from the noise,in order to further effectively reduce the noise of the micro-seismic signal containing noise,it is necessary to combine other algorithms for noise reduction processing.In order to achieve the purpose of effective noise reduction and the preservation of micro-seismic signal characteristics in actual signal processing,based on the VMD algorithm,based on the research of micro-seismic signal characteristics,the VMD based on signal spectrum features is proposed.Wavelet packet noise reduction algorithm.Firstly,according to the characteristics of VMD algorithm decomposition and the advantages of wavelet packet de-noising algorithm,a noise reduction algorithm based on VMD and wavelet packet is proposed.Then,based on the spectral characteristics of the micro-seismic signal,a series of modal components obtained by VMD decomposition are used based on the signal.The modal selection method of the spectral features is selected,and finally the wavelet packet de-noising is performed on the selected useful modal components.The experimental analysis proves that using the proposed algorithm to de-noise the noise-containing micro-seismic signal can obtain higher signal-to-noise ratio and lower root mean square error while retaining signal characteristics.