Zhang Yiming, Guo Ping
School of Computer Science, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Sensors (Basel). 2025 Jul 24;25(15):4593. doi: 10.3390/s25154593.
Coastal areas are prone to thunderstorms. Lightning strikes can damage power facilities and communication systems, thereby leading to serious consequences. The lightning location network achieves lightning location through data fusion from multiple lightning locator nodes and can detect the location and intensity of lightning in real time. It is an important facility for thunderstorm warning and protection in coastal areas. However, when a sensor node in a lightning location network experiences a soft fault, it causes distortion in the lightning location. To achieve fault diagnosis of lightning locator nodes in a multi-node data fusion mode, this study proposes a new lightning location mode: the observer pattern. This paper first analyzes the main factors contributing to the error of the lightning location algorithm under this mode, proposes an observer pattern estimation algorithm (OPE) for lightning location, and defines the proportion of improvement in lightning positioning accuracy (PI) caused by the OPE algorithm. By analyzing the changes in PI in the process of lightning location, this study further proposes a diagnostic algorithm (OPSFD) for soft-fault nodes in a lightning location network. The simulation experiments in the paper demonstrate that the OPE algorithm can effectively improve the positioning accuracy of existing lightning location networks. Therefore, the OPE algorithm is also a low-cost and efficient method for improving the accuracy of existing lightning location networks, and it is suitable for the actual deployment and upgrading of current lightning locators. Meanwhile, the experimental results show that when a soft fault causes the observation error of the node to exceed the normal range, the OPSFD algorithm proposed in this study can effectively diagnose the faulty node.
沿海地区容易发生雷暴。雷击可能会损坏电力设施和通信系统，从而导致严重后果。雷电定位网络通过多个雷电定位器节点的数据融合来实现雷电定位，并能实时检测雷电的位置和强度。它是沿海地区雷暴预警和防护的重要设施。然而，当雷电定位网络中的一个传感器节点出现软故障时，会导致雷电定位出现偏差。为了在多节点数据融合模式下实现雷电定位器节点的故障诊断，本研究提出了一种新的雷电定位模式：观察者模式。本文首先分析了该模式下雷电定位算法误差的主要影响因素，提出了一种用于雷电定位的观察者模式估计算法（OPE），并定义了OPE算法引起的雷电定位精度提高比例（PI）。通过分析雷电定位过程中PI的变化，本研究进一步提出了一种雷电定位网络中软故障节点的诊断算法（OPSFD）。文中的仿真实验表明，OPE算法能够有效提高现有雷电定位网络的定位精度。因此，OPE算法也是一种低成本、高效的提高现有雷电定位网络精度的方法，适用于当前雷电定位器的实际部署和升级。同时，实验结果表明，当软故障导致节点的观测误差超出正常范围时，本研究提出的OPSFD算法能够有效诊断出故障节点。
