This paper introduces KG-FLoc, a knowledge graph-enhanced framework for secondary circuit fault localization in intelligent substations. The proposed KG-FLoc innovatively formalizes secondary components (e.g., circuit breakers, disconnectors) as graph nodes and their multi-dimensional relationships (e.g., electrical connections, control logic) as edges, constructing the first comprehensive knowledge graph (KG) to structurally and operationally model secondary circuits. By reframing fault localization as a knowledge graph link prediction task, KG-FLoc identifies missing or abnormal connections (edges) as fault indicators. To address dynamic topologies and sparse fault samples, KG-FLoc integrates two core innovations: (1) a relation-aware gated unit (RGU) that dynamically regulates information flow through adaptive gating mechanisms, and (2) a hierarchical graph isomorphism network (GIN) architecture for multi-scale feature extraction. Evaluated on real-world datasets from 110 kV/220 kV substations, KG-FLoc achieves 97.2% accuracy in single-fault scenarios and 93.9% accuracy in triple-fault scenarios, surpassing SVM, RF, MLP, and standard GNN baselines by 12.4–31.6%. Beyond enhancing substation reliability, KG-FLoc establishes a knowledge-aware paradigm for fault diagnosis in industrial systems, enabling precise reasoning over complex interdependencies.

The dynamic behaviour of rain droplets on the insulator surface is a key measure to its reliability and performance. This is due to the fact that the presence and motion of rain droplets cause intensive discharge activities, such as corona and low current arcing, which accelerate the ageing process and flashovers. This article aims to investigate and characterize the movement of a rain droplet placed on an inclined insulator surface subject to an intensive electric field. The rain droplets’ movement on hydrophobic surfaces in the absence of an electric field is investigated. A high speed camera is used to capture the footage and finite element method (FEM) is used to simulate the multi-physics phenomenon on two polymeric surfaces, namely, silicon rubber (SiR) and PTFE (polytetrafluoroethylene). A ‘creepage’ motion was observed. The inception of motion and the movement speed are analysed in correlation with various surface conditions. Models are established to estimate the moisture and potential discharge characteristics on the inclined polymeric surfaces. They are further utilized to analyse the actual insulators subject to wet conditions.