Utilized fundamental theory and analysis method of Incomplete Information repeated games, introduced Incomplete Information into repeated games, and established two stages dynamic games model of the local authority an...Utilized fundamental theory and analysis method of Incomplete Information repeated games, introduced Incomplete Information into repeated games, and established two stages dynamic games model of the local authority and the coal mine owner. The analytic result indicates that： so long as the country established the corresponding rewards and punishments incentive mechanism to the local authority departments responsible for the work, it reports the safety accident in the coal mine on time. The conclusion that the local government displays right and wrong cooperation behavior will be changed with the introduction of the Incomplete Information. Only has the local authority fulfill their responsibility, can the unsafe accident be controlled effectively. Once this kind of cooperation of local government appears, the costs of the country on the safe supervise and the difficulty will be able to decrease greatly.展开更多
Coal bumps have long been a safety hazard in coal mines, and even after decades of research, the exact mechanics that cause coal bumps are still not well understood. Therefore, coal bumps are still difficult to predic...Coal bumps have long been a safety hazard in coal mines, and even after decades of research, the exact mechanics that cause coal bumps are still not well understood. Therefore, coal bumps are still difficult to predict and control. The LaModel program has a long history of being used to effectively analyze displacements and stresses in coal mines, and with the recent addition of energy release and local mine stiffness calculations, the LaModel program now has greatly increased capabilities for evaluating coal bump potential. This paper presents three recent case histories where coal stress, pillar safety factor, energy release rate and local mine stiffness calculations in LaModel were used to evaluate the pillar plan and cut sequencing that were associated with a number of bumps. The first case history is a longwall mine where a simple stress analysis was used to help determine the limiting depth for safely mining in bump-prone ground. The second case history is a room-and-pillar retreat mine where the LaModel analysis is used to help optimize the pillar extraction sequencing in order to minimize the frequent pillar line bumps. The third case history is the Crandall Canyon mine where an initial bump and then a massive pillar collapse/bump which killed 6 miners is extensively back-analyzed. In these case histories, the calculation tools in LaModel are ultimately shown to be very effective for analyzing various aspects of the bump problem, and in the conclusions, a number of critical insights into the practical calculation of mine failure and stability developed as a result of this research are presented.展开更多
随着人工智能和无人驾驶等相关学科的快速发展,煤矿装备的智能化和无人化成为了新的趋势。智能设备的应用将大幅提高煤矿作业的生产力以及人员安全性。露天煤矿地形复杂,与城市环境相比无明显的几何特征,具有分段相似性,利用现有以激光...随着人工智能和无人驾驶等相关学科的快速发展,煤矿装备的智能化和无人化成为了新的趋势。智能设备的应用将大幅提高煤矿作业的生产力以及人员安全性。露天煤矿地形复杂,与城市环境相比无明显的几何特征,具有分段相似性,利用现有以激光雷达为主的同时定位与建图(Simultaneous Localization and Mapping,SLAM)方案在该环境下易出现定位漂移和建图误差较大等现象。针对上述问题,提出了一种基于激光雷达(Light Detection and Ranging,LiDAR)和惯导(Inertial Measurement Unit,IMU)紧耦合的SLAM算法,该算法使用LiDAR和IMU两种传感器作为数据输入,对数据进行预处理,前端利用迭代扩展卡尔曼滤波器将预处理后的LiDAR特征点与IMU数据相融合,并使用后向传播来矫正雷达运动畸变,后端利用雷达相对位姿因子将LiDAR帧间配准结果作为约束因子与回环因子共同完成全局因子图优化。利用开源数据集和露天煤矿实地数据集验证了算法的鲁棒性和精确性。试验结果表明在城市结构化环境中文中所提算法与当前激光SLAM算法精度保持一致,而针对长达两千多米的露天煤矿实地环境,所提算法较FAST-LIO2、LIO-SAM紧耦合算法在定位精度上分别提高了46.00%和23.15%,且具有更高的鲁棒性。展开更多
文摘Utilized fundamental theory and analysis method of Incomplete Information repeated games, introduced Incomplete Information into repeated games, and established two stages dynamic games model of the local authority and the coal mine owner. The analytic result indicates that： so long as the country established the corresponding rewards and punishments incentive mechanism to the local authority departments responsible for the work, it reports the safety accident in the coal mine on time. The conclusion that the local government displays right and wrong cooperation behavior will be changed with the introduction of the Incomplete Information. Only has the local authority fulfill their responsibility, can the unsafe accident be controlled effectively. Once this kind of cooperation of local government appears, the costs of the country on the safe supervise and the difficulty will be able to decrease greatly.
文摘Coal bumps have long been a safety hazard in coal mines, and even after decades of research, the exact mechanics that cause coal bumps are still not well understood. Therefore, coal bumps are still difficult to predict and control. The LaModel program has a long history of being used to effectively analyze displacements and stresses in coal mines, and with the recent addition of energy release and local mine stiffness calculations, the LaModel program now has greatly increased capabilities for evaluating coal bump potential. This paper presents three recent case histories where coal stress, pillar safety factor, energy release rate and local mine stiffness calculations in LaModel were used to evaluate the pillar plan and cut sequencing that were associated with a number of bumps. The first case history is a longwall mine where a simple stress analysis was used to help determine the limiting depth for safely mining in bump-prone ground. The second case history is a room-and-pillar retreat mine where the LaModel analysis is used to help optimize the pillar extraction sequencing in order to minimize the frequent pillar line bumps. The third case history is the Crandall Canyon mine where an initial bump and then a massive pillar collapse/bump which killed 6 miners is extensively back-analyzed. In these case histories, the calculation tools in LaModel are ultimately shown to be very effective for analyzing various aspects of the bump problem, and in the conclusions, a number of critical insights into the practical calculation of mine failure and stability developed as a result of this research are presented.
文摘随着人工智能和无人驾驶等相关学科的快速发展,煤矿装备的智能化和无人化成为了新的趋势。智能设备的应用将大幅提高煤矿作业的生产力以及人员安全性。露天煤矿地形复杂,与城市环境相比无明显的几何特征,具有分段相似性,利用现有以激光雷达为主的同时定位与建图(Simultaneous Localization and Mapping,SLAM)方案在该环境下易出现定位漂移和建图误差较大等现象。针对上述问题,提出了一种基于激光雷达(Light Detection and Ranging,LiDAR)和惯导(Inertial Measurement Unit,IMU)紧耦合的SLAM算法,该算法使用LiDAR和IMU两种传感器作为数据输入,对数据进行预处理,前端利用迭代扩展卡尔曼滤波器将预处理后的LiDAR特征点与IMU数据相融合,并使用后向传播来矫正雷达运动畸变,后端利用雷达相对位姿因子将LiDAR帧间配准结果作为约束因子与回环因子共同完成全局因子图优化。利用开源数据集和露天煤矿实地数据集验证了算法的鲁棒性和精确性。试验结果表明在城市结构化环境中文中所提算法与当前激光SLAM算法精度保持一致,而针对长达两千多米的露天煤矿实地环境,所提算法较FAST-LIO2、LIO-SAM紧耦合算法在定位精度上分别提高了46.00%和23.15%,且具有更高的鲁棒性。
