CCTEG Ecological Environment Technology Co., Ltd.
School of Automation, China University of Geosciences
Faculty of Engineering, China University of Geosciences

为了探明煤矿采空区覆岩破坏类型与裂隙发育情况，快速准确划分采空区覆岩弯曲带、断裂带、垮落带(简称“三带”)，提出智能识别方法，为制定采空区治理方案提供依据。以山东某矿区采空区为例，采用贝叶斯在线变化点检测(Bayesian Online Changepoint Detection，BOCD)算法对钻进过程中的冲洗液漏失量和钻速数据在煤矿采空区“三带”界限处的变化及响应特征进行分析。以勘察规范中有关“三带”高度计算经验公式作为约束条件，对冲洗液漏失量和钻速数据中的候选变化点进行检测、优选，进而确定煤矿采空区“三带”界限深度。智能识别的结果与实际值吻合，其中，弯曲带下限、断裂带下限、垮落带下限的深度误差分别为+0.67、+0.31和+0.52 m，弯曲带、断裂带和垮落带的高度误差分别为+0.14%、−0.63%和+2.49%。基于钻进数据的采空区覆岩“三带”智能识别方法精度满足设计需要，切实可行。该方法将钻进数据与经验公式相结合，在钻进过程中即可完成“三带”界限的划分，充分发挥数据的时效性，避免了技术人员主观判断对识别结果产生影响。相较于依靠多种方式综合确定“三带”界限的传统方法，该智能识别方法显著提高了“三带”划分的时效性和准确性。

In this paper, an intelligent identification method was proposed to ascertain overlying strata failure types and fracture development in the overlying strata of a goaf, and identify three zones (sagging zone, fractured zone and caving zone) quickly and accurately. This method is expected to be a basis in later development of goaf treatment plans. A coal mine goaf in Shandong Province was introduced for case study, where the Bayesian Online Changepoint Detection (BOCD) algorithm was employed to analyze the changes and response characteristics of the drilling fluid loss and drilling rate over the drilling process at the boundaries of three zones. With exploration specification empirical formulas for calculating the heights of three zones as constraints, the candidate changepoints were detected and optimized from the drilling fluid loss and drilling rate data. Then, the boundary depths of three zones of the goaf were determined. The intelligent identification results are in good coincidence with the actual values. Specifically speaking, the depth errors of the lower boundaries of sagging zone, fractured zone and caving zone are +0.67 m, +0.31 m, and +0.52 m, and the height errors of sagging zone, fractured zone and caving zone are +0.14% and −0.63% and +2.49%. The intelligent identification method for overlying strata three zones of a goaf based on drilling data is demonstrated to be acceptable in accuracy and available for use. The proposed method presents a good combination of drilling data with empirical formulas, which permits boundary division of three zones during drilling, full play of data timeliness and elimination of impacts arising from technicians’ subjective judgment on the identification results. Superior to conventional techniques referring multiple methods to identify the boundaries of three zones, the intelligent identification method significantly enhances the timeliness and accuracy of three zones division.

中煤科工循环产业研究院(山东)有限公司项目(0206STSD0002)

李建文，赵文，吴振坤，等. 煤矿采空区覆岩“三带”智能识别方法[J]. 煤田地质与勘探，2024，52(4)：1−8.

LI Jianwen，ZHAO Wen，WU Zhenkun，et al. Intelligent identification method for overburden three zones of a goaf[J]. Coal Geology & Exploration，2024，52(4)：1−8.