Bond Graph Model Based Fault Detection and Isolation for Locomotive Brake

Abstract:

The train locomotive brake pneumatic equalizer control (PEC) unit was analyzed using the bond graph dynamic modeling. The created fault bond graph was utilized to deduce analytical redundancy relations (ARRs). The whole fault signature matrix (FSM) was extracted. Besides, online monitoring using sequential probability ratio test (SPRT) was exerted to check the anomaly occurrence of the unit components. When any alert was triggered, the generated synthesized non null coherence vector was matched with the FSM to detect and isolate the possible faulty components. A simulation experiment was conducted to illustrate the feasibility of the proposed methodology.