Shield leg pressure data from all shields and shearer location with time stamp from a mechanized longwall face are monitored and recorded in a surface computer. These data contain random noise due to power failure, leakage of legs, bad sensor reading and other maintenance or geo-mechanical problems. An algorithm is developed to detect mining cycle parameters such as setting and final pressures and duration of the cycle from these data for the analysis of periodic roof weighting phenomena. The intensities and persistence of periodic roof weighting are the vital information to the mine management to take judicious decision on longwall operation. The paper presents details of the algorithm which identifies 96% of mining cycles from the noisy data belonging to consecutive 5 months or 410 m of face advancement. Based on this analysis, 2 types of periodic roof weighting phenomena are detected, namely, (i) normal type—having peak intensity of 75 to 90% of yield pressure, interval of occurrences of about 10 to 15 m with persistence of 3 to 4 m and (ii) severe type—peak intensity over 90% of yield pressure, interval of 25 to 40 m with persistence of over 10 m. It is envisaged that these phenomena have direct relationship with main roof thickness, its overhung length and material properties.

中文翻译：

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使用监测的长壁盾构压力和采煤机位置评估采矿循环参数和分析周期性顶板加权的算法

来自机械化长壁工作面的所有盾构和采煤机位置的盾构腿压力数据被监控并记录在地面计算机中。这些数据包含由于电源故障、支腿泄漏、传感器读数不良和其他维护或地质力学问题造成的随机噪声。开发了一种算法来从这些数据中检测采矿循环参数，例如设置和最终压力以及循环持续时间，以分析周期性顶板加权现象。定期顶板加权的强度和持续性是矿山管理层对长壁作业做出明智决策的重要信息。本文介绍了该算法的详细信息，该算法从属于连续 5 个月或 410 m 的工作面推进的噪声数据中识别 96% 的挖掘周期。基于这一分析，检测到2种周期性顶板加权现象，即(i)正常型——峰值强度为屈服压力的75%至90%，发生间隔约10至15 m，持续时间为3至4 m；(ii)严重型——峰值强度超过屈服压力的 90%，间隔 25～40 m，持续时间超过 10 m。预计这些现象与主屋顶厚度、悬垂长度和材料特性有直接关系。