A Soft-Fault Diagnosis Method for Coastal Lightning Location Networks Based on Observer Pattern

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.