Xi’an Research Institute,China Coal Technology & Engineering Group Corp. ,Xi’an　 710077,China

Evaluation of surrounding rock characteristics using drilling parameters can provide support for safe and green coal mining. Due to the significant difficulty and low accuracy in lithology identification during exploration in un- derground coal mine roadway,a fuzzy identification method for coal-bearing strata based on the Kernel Fuzzy C-means (KFCM) clustering of drilling parameters is proposed. In combination with simulated rock sample drilling tests con- ducted on the drilling bench,some training samples aimed at understanding sensitive drilling parameters such as drill-ing rate,rotation speed,and bit pressure are obtained. The KFCM algorithm is used to analyze drilling parameter training samples,and a drilling parameter sample space is constructed and mapped to high-dimensional space for cluste- ring. The distribution structures in the weak interlayer,coal seam,and mudstone layer and the corresponding clustering centers are determined using a Gaussian kernel function. Compared to the linear kernel function,the vertical classifica- tion of the Gaussian kernel function better aligns with the characteristics of sedimentary rock structure,and clustering time is reduced by 7. 2% . Based on the clustering results of the drilling parameters,the drilling rate is taken as the key parameter to measure the drilling performance of multiple rock types. By analyzing variation in the drilling parameter data set,a prediction model for drilling rate with a power function of bit pressure and rotation speed is established. The spatial division of typical weak interlayer coal seam and mudstone layer is completed using data interpolation. The membership formula of the drilling rate in a typical coal-bearing formation is obtained by constructing the subsection triangle membership function of drilling rate using the fuzzy mathematical method. According to the membership formu- la,the lithology is divided into five grades,which help to realize the fuzzy identification different lithologies. The validi- ty of the proposed method is verified using a practical drilling experiment. Results show that this method can quickly identify the lithology of typical coal-bearing strata under a rotary PDC anchor bit,with an accuracy of 92% . The preset research provides an effective method for identifying potential disaster causing factors in coal mine roadway.

国家自然科学基金资助项目(51774320)

ZHANG Youzhen,ZHANG Ning,SHAO Junjie,et al. Fuzzy identification of coal-bearing strata lithology based on drill- ing parameter clustering[J]. Journal of China Coal Society,2019,44 (8):2328 - 2335.