Drilling elastic wave processing and coal-rock identification method based on EWOA-VMD
Focused on the urgent demand for equipment and techniques for coal-rock interface i-dentification in current intelligent coal mining,this paper proposes a coal-rock identification technique that utilizes borehole space for elastic wave detection to determine coal seam thick-ness and coal-rock interface position.This technology aims to address the challenges faced by current coal rock recognition technology,including low recognition accuracy and efficiency due to the influence of coal mine geological conditions and complex construction environments.In response to the critical issue of limited identification of characteristic information of coal-rock interface reflection echo in elastic wave echo signals due to various noise interferences in the underground environment,this paper presents a combined optimization algorithm based on en-hanced whale optimization algorithm(EWOA)and variational mode decomposition(VMD).Initially,EWOA is proposed,building upon the optimization of three search strategies and the introduction of a pooling mechanism in the original WOA.The EWOA employs the minimum envelope entropy as its fitness function to adaptively solve the optimization problem of the crit-ical parameter combination(k,α)required for VMD.The correlation coefficient threshold method is integrated to identify components within the intrinsic mode function(IMF)set that contain coal-rock interface feature information.Subsequently,simulation signals are constructed based on the characteristics of borehole elastic wave signals.This algorithm,along with the ensemble empirical mode decomposition(EEMD)and complete ensemble empirical mode decomposition(CEEMD)methods,is utilized for signal processing.The effectiveness of the proposed algorithm is validated through the comparison of evaluation metrics such as root mean square error,normalized correlation coefficient and signal-to-noise ratio.Finally,the al-gorithm is applied to process complex elastic wave echo signals obtained from indoor model ex-periments.The results indicate that the algorithm can accurately identify coal-rock interface re-flection echo signals in measured complex echoes.The error in coal seam thickness is within 12 mm,and the average error in coal-rock interface position is 2.5％.This demonstrates the ef-fectiveness and reliability of the proposed algorithm in handling real-world scenarios with com-plex echo signals.This algorithm provides a valuable reference for the processing of non-sta-tionary and nonlinear complex elastic wave echo signals,and it contributes to the advancement of borehole elastic wave detection technology in coal-rock interface identification.
NETL
NSTL
万方数据
