發(fā)布時(shí)間：2018-05-01 04:33

  本文選題：微震 + EMD��； 參考：《中南大學(xué)學(xué)報(bào)(自然科學(xué)版)》2017年01期

【摘要】：針對現(xiàn)有礦山微震監(jiān)測系統(tǒng)信號(hào)自動(dòng)識(shí)別難的問題,提出基于經(jīng)驗(yàn)?zāi)�態(tài)分解(EMD)和形態(tài)分形維數(shù)的識(shí)別方法。首先,采用EMD將原始信號(hào)分解為若干個(gè)本征模態(tài)分量(IMF),選擇前5個(gè)分量進(jìn)行重構(gòu)得到新的信號(hào)。其次,求出處理后信號(hào)的形態(tài)學(xué)分形維數(shù),利用微震波形和爆破波形分形維數(shù)的差異進(jìn)行信號(hào)識(shí)別。對50組微震波形和50組爆破波形進(jìn)行試驗(yàn)研究。對比未經(jīng)EMD處理的形態(tài)學(xué)分形維數(shù)以及經(jīng)EMD處理的盒維數(shù)識(shí)別結(jié)果。研究結(jié)果表明:50組微震波形和50組爆破波形在形態(tài)學(xué)分形維數(shù)為1.4時(shí)具有較高的識(shí)別率;微震波形維數(shù)主要在1.4以下,爆破波形維數(shù)則基本高于1.4;EMD結(jié)合形態(tài)學(xué)分形維數(shù)的識(shí)別效果最好,為微震監(jiān)測波形識(shí)別提供了新途徑。
[Abstract]:Aiming at the difficulty of automatic signal recognition in the existing mine microseismic monitoring system, an identification method based on empirical mode decomposition (EMD) and fractal dimension of morphology is proposed. Firstly, the original signal is decomposed into several intrinsic mode components by EMD, and the first five components are selected to reconstruct the new signal. Secondly, the fractal dimension of the processed signal is obtained, and the difference of fractal dimension between the microseismic waveform and the blasting waveform is used to recognize the signal. Experimental study on 50 sets of microseismic waveforms and 50 groups of blasting waveforms was carried out. The fractal dimension of morphology without EMD and the recognition result of box dimension treated by EMD were compared. The results show that the recognition rate of microseismic waveforms and blasting waveforms of 50 groups are higher when the fractal dimension of morphology is 1.4, and the dimension of microseismic waveforms is mainly below 1.4. The blasting waveform dimension is higher than 1.4 EMD combined with morphological fractal dimension, which provides a new way for microseismic monitoring waveform recognition.
【作者單位】： 中南大學(xué)資源與安全工程學(xué)院;
【基金】：國家自然科學(xué)基金資助項(xiàng)目(51374244)~~
【分類號(hào)】：TD76

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