Diagnosis Method for Local Insulation Deterioration of DC Traction Power Systems Based on Sectional Diagnosis Model

Insulation deterioration between rails and ground in DC traction power systems can lead to significant stray current leakage, causing corrosion to buried metal pipelines and affecting the long-term stable and safe operation of the system. To identify insulation deteriorated rail sections and address this issue, a diagnostic method for localized rail insulation deterioration is proposed. Firstly, this paper presents an DC traction power systems model under localized insulation deterioration conditions, and further establishes a rail insulation sectional diagnosis model. Then, by integrating the sectional diagnosis model with a hybrid Genetic Algorithm-Particle Swarm Optimization (GAPSO) method, the mathematical model of rail potential in the sectional diagnosis model is derived, and diagnostic procedures for rail-to-ground insulation deterioration are designed. Finally, A insulation deterioration diagnosis method for DC traction power systems based on the sectional diagnosis model is proposed. The method is validated through simulations using actual line data. Results demonstrate that the proposed method can effectively monitor rail insulation status and accurately identify insulation deteriorated zones.