随掘地震是利用掘进机切割岩石产生的振动作为震源来进行探测，具有安全、简便、高效等优点，但随掘地震探测所采集的地震记录中波组成分复杂，有效信号能量弱，且被掘进机工作时产生的强噪声干扰，信噪比极低，去噪难度大，需要对随掘地震记录去噪方法进行研究。通过改进人工蜂群（IABC）算法搜索策略，提高了人工蜂群算法的收敛速度和收敛精度，将改进人工蜂群算法作为独立分量分析（ICA）方法的优化算法，提高独立分量分析方法的信噪分离效果。建立随掘地震超前探测地质-地球物理模型，给定加噪的变频变幅连续信号作为随掘地震震源子波，采用有限差分法进行数值模拟，得到随掘地震的地震记录，并在仿真地震记录中加入随机噪声；采用基于改进人工蜂群的独立分量分析方法（IABC-ICA）进行噪声与有效信号的分离，在此基础上利用互相关和脉冲反褶积方法进行压缩子波处理，得到与采用雷克子波震源模拟地震记录一致的波场特征，验证了该方法的去噪效果。结合现场试验的实测数据，进行IABC-ICA去噪、互相关、反褶积等处理，从信噪比较低的实际地震记录中提取了有效波信号。研究表明：基于改进人工蜂群的独立分量分析方法能够较好地分离随掘地震记录中的有效信号和干扰噪声信号，改善随掘地震有效信号的提取质量。

Mine seismic while drilling exploration use the vibration generated by the cutting rock of the roadheader as the source to detect,which has the advantages of safety,simplicity and efficiency. However,the seismic records collected by mine seismic while drilling detection are complex in wave composition,weak in effective signal energy,and strong noise interference generated by the tunneling machine. The signal and noise ratio are extremely low,and the denoising is difficult. It is necessary to study the denoising method of the tunneling along with the mine seismic while drilling records. By improving the search strategy of artificial bee colony (IABC) algorithm,the convergence speed and accuracy of artificial bee colony algorithm are improved. The improved artificial bee colony algorithm is used as the optimization algorithm of independent component analysis (ICA) method to improve the signal and noise separation effect of independent component analysis. The geologicalgeophysical model of the advance detection of the excavation earthquake is established,and the noised variable frequency amplitude continuous signal is given as the source wavelet of the mine seismic while drilling. The finite difference method is used for numerical simulation to obtain the seismic record of the mine seismic while drilling,and the random noise is added into the simulation seismic record. The independent component analysis method based on improved artificial bee colony (IABC-ICA) was used to separate the noise and effective signal. On this basis,the crosscorrelation and pulse deconvolution methods were used to process the compressed wavelet,and the wave field characteristics consistent with the seismic records simulated by the Ricker wavelet source were obtained,which verified the denoising effect of this method. Combined with the field test data,IABC-ICA denoising,cross correlation,deconvolution and other processing are carried out to extract the effective wave signal from the actual seismic records with low signal and noise ratio. The study shows that the independent component analysis method based on improved artificial bee colony can better separate the effective signal and interference noise signal in the record with mine seismic while drilling,and improve the extraction quality of the effective signal.

1 基于改进人工蜂群的独立分量分析方法

   1.1 独立分量分析方法

   1.2 改进人工蜂群算法

   1.3 IABC-ICA方法

2 基于IABC-ICA方法的信号分离

3 随掘地震超前探测数值模拟

   3.1 地质-地球物理模型

   3.2 数值模拟

   3.3 数值模拟结果分析

4 数值模拟地震记录的有效信号提取

   4.1 噪声与有效信号的分离

   4.2 连续信号子波的压缩

5 现场试验

   5.1 工程概况

   5.2 数据处理与分析

6 结论