The rapid increase of train speed has brought greater challenges to the safety and reliability of railway systems. Therefore, it is necessary to monitor the operation status of trains, infrastructure, and their operating environment in real time. Because the operation environment of railway systems is complex, the construction cost of wired monitoring systems is high, and it is difficult to achieve full coverage in the operation area of harsh environments, so wireless sensor networks are suitable for the status monitoring of railway systems. Energy resources of nodes are the basis of ensuring the lifecycle of wireless sensor networks, but severely restrict the sustainability of wireless sensor networks. A construction method of special wireless sensor networks for railway status monitoring, and an optimal energy resources allocation method of wireless sensor networks for intelligent railway systems are proposed in this paper. Through cluster head selection and rotating probability model, clustering generation and optimization model, and partial coverage model, the energy consumption of nodes can be minimized and balanced. The result of simulation experiment proved that the lifetime of wireless sensor networks can be maximized by the optimal energy resources allocation method based on clustering optimization and partial coverage model, based on polynomial time algorithm.

中文翻译：

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智能铁路系统无线传感器网络的能源优化分配方法。

火车速度的迅速提高对铁路系统的安全性和可靠性提出了更大的挑战。因此，有必要实时监视火车，基础设施及其运行环境的运行状态。由于铁路系统的运行环境复杂，有线监控系统的建设成本较高，在恶劣环境的运营区域难以实现全覆盖，因此无线传感器网络非常适合铁路系统的状态监控。节点的能量资源是确保无线传感器网络生命周期的基础，但严重限制了无线传感器网络的可持续性。一种铁路状态监测专用无线传感器网络的构建方法，提出了一种智能铁路系统无线传感器网络的最优能源分配方法。通过群集头选择和旋转概率模型，群集生成和优化模型以及部分覆盖模型，可以使节点的能耗最小化和平衡。仿真实验结果表明，基于多项式时间算法的聚类优化和部分覆盖模型的最优能源分配方法可以最大化无线传感器网络的寿命。节点的能量消耗可以最小化和平衡。仿真实验结果表明，基于多项式时间算法的聚类优化和部分覆盖模型的最优能源分配方法可以最大化无线传感器网络的寿命。节点的能量消耗可以最小化和平衡。仿真实验结果表明，基于多项式时间算法的聚类优化和部分覆盖模型的最优能源分配方法可以最大化无线传感器网络的寿命。