Fault diagnosis of electric railway traction substation with model-based relation guiding algorithm

Most diagnosis systems used in electric railway traction substation are expert systems based on experience, which cannot diagnose faults beyond experience and are very difficult for transplantation and maintenance. In this paper, the model-based diagnosis (MBD) with integration reasoning is firstly used for fault diagnosis of electric railway traction substation. Aiming at the structural characteristics and actual demands of traction substation, we propose a detailed application plan. Rules for element and system models are established. In addition, we propose a relation guiding algorithm (RGA) for searching candidates of minimal conflict set, in which the hidden messages of analytical redundancy relations can be made full use of and the searching space is reduced further. Taking the autotransformer (AT) traction substation in Hefei–Nanjing Passenger Link of China Railway as an example, we construct models for different device objects, and give the descriptions of system model in traction substation. Based on a sequence of fault observations, the fault diagnosis is tested with the proposed plan. The diagnosis result shows that the application plan with MBD and integration reasoning is feasible and effective for traction substation.