School of Electronic and Information Engineering, Beijing Jiaotong University
China Coal Research Institute
School of Information and Control Engineering, China University of Mining and Technology

煤矿物联网在煤矿生产监测控制和灾害预测预警中具有重要意义。然而，煤矿物联网在数据传输过程中很容易受到煤矿事故的影响，事故往往会导致部分物联网节点损毁，残存的物联网节点受限于较低的数量和能量约束，难以完成对事故巷道中大量监测数据的采集和传输任务。为了保证灾后煤矿物联网可靠、节能的数据通信，构建了一种无人机(UAV, Unmanned Aerial Vehicle)辅助的分簇式煤矿物联网通信系统架构。在此架构基础上，提出了一种基于分簇和A*搜索的UAV辅助数据采集方法。首先，利用物联网节点的能耗和UAV的路径长度构造目标函数，通过分别绘制节点到簇中心的距离方差、UAV数据采集的路径长度和不同K值之间的关系图来确定最优分簇数K。然后，采用K均值算法将所有物联网节点划分为K个簇。接着，通过综合考虑物联网节点的数据采集能耗和UAV的数据采集能耗，将UAV的路径规划问题建立为一个最小化煤矿物联网数据采集系统整体能耗的优化问题，并提出了一种改进的A*搜索UAV数据采集路径规划算法。在该算法中，利用指针网络将UAV的起始点和所有分簇的信息输入到A*网络中，A*网络输出的一组簇头和簇头访问顺序即为UAV的飞行路径。仿真结果表明，与平面式UAV数据采集方法相比，所提方法显著降低了UAV的能耗；与两种分簇式UAV数据采集方法相比，所提方法有效降低了物联网节点的平均能耗和总能耗。因此，所提UAV辅助的数据采集方法改善了灾后煤矿物联网系统的能耗问题，延长了网络生存期，对于提高灾后煤矿物联网数据采集系统的可靠性起到了重要作用。

Mine Internet of Things (MIoT) is of great significance in mine production monitoring and disaster prediction. However, the MIoT is easily affected by mine accidents in data transmission. Accidents often lead to the damage of IoT nodes (IoTN). The surviving IoTNs are limited by low quantity and energy, so it is difficult to complete the task of collecting and transmitting a large number of monitoring data in the roadway. In order to ensure the reliable and energy-efficient data communication of MIoT after disaster, an unmanned aerial vehicle (UAV)-assisted clustered MIoT communication system architecture is established. Based on this, an UAV-assisted data gathering method based on clustering and A* search is proposed. Firstly, the energy consumption of IoTNs and the path length of UAV are considered to construct the objective function. The optimal K is determined by plotting the relationship between the variance distance from the node to the cluster center and the path length of UAV data gathering and different K values. Then the K-means algorithm is used to divide all IoTNs into K clusters. Next, by considering the data gathering energy consumption of UAV and IoTNs, the path planning problem of UAV is established as an optimization problem to minimize the overall energy consumption of MIoT system, and an improved A* search algorithm for UAV data collection path planning is proposed. In this algorithm, the starting point of UAV and all clustering information are input into A * network by using the pointer network. A group of sorted cluster heads output by A * network is the flight path of UAV. Simulation results show that compared with the flat-based UAV data gathering method, the proposed data gathering method significantly reduces the energy consumption of UAV; Compared with two clustered-based UAV data acquisition methods, the proposed method effectively reduces the average and total energy consumption of IoTNs. Therefore, the proposed UAV-assisted data gathering method improves the energy consumption of the MIoT system after disaster, prolongs the network lifetime, and plays an important role in improving the reliability of the MIoT data gathering system after disaster.

国家自然科学基金面上资助项目（51874299）

赵　清，杨　维，张立亚，等. 灾后煤矿物联网无人机辅助节能数据采集方法[J]. 煤炭科学技术，2023，51（8）：228−238

ZHAO Qing，YANG Wei，ZHANG Liya，et al. UAV-assisted energy-efficient data gathering method of mine IoT after disaster[J]. Coal Science and Technology，2023，51（8）：228−238