矿井安全的短期预警及完备性监测算法(英文)

提出一种新的矿井安全短期预警及完备性监测模型。通过Kalman滤波提取真实GPS动态变形信息,并构建双边累积和检验统计量,建立短期预警模型,进而提高预警系统的可靠性。通过分析预警模型的可得性(最小预警变形)、误警率(平均运行长度)及漏警率(预警延迟)与预警参数之间的关系,给出预警参数的选取方法。变形试验平台模拟实验表明,预警模型能够有效用于陡坡变形预警。山西马兰矿矿井实测变形数据研究表明:本预警算法能够有效地探测微小变形及变形发生的时刻,在给定预警参数(最小预警灾害变形为15 mm,平均运行长度为1000)的条件下,本算法探测出相邻两天的变形发生时刻分别为第705历元(705 s)和517历元(517 s)。

Short-term warning and integrity monitoring algorithm for coal mine shaft safety

A new short-term warning and integrity monitoring algorithm was proposed for coal mine shaft safety. The Kalman filter (KF) model was used to extract real global positioning system (GPS) kinematic deformation information. The short-term warning model was built by using the two-side cumulative sum (CUSUM) test, which further improves the warning system reliability. Availability (the minimum warning deformation, MWD), false alarm rate (the average run length, ARL), missed rate (the warning delay, WD) and the relationships among them were analyzed and the method choosing warning parameters is given. A test of a deformation simulation platform shows that the warning algorithm can be effectively used for steep deformation warning. A field experiment of the Malan mine shaft in Shanxi coal area illustrates that the proposed algorithm can detect small dynamic changes and the corresponding occurring time. At given warning thresholds (MWD is 15 mm and ARL is 1000), the detected deformations of two consecutive days’ deformation sequences with the algorithm occur at the 705th epoch (705 s) and the 517th epoch (517 s), respectively.