Abstract: Due to many kinds of railway passenger transport equipments and scattered distribution area, the work efficiency of manual inspection was low. In order to improve the efficiency of the inspection working and implement the intelligent inspection work for the equipments, this article proposed and designed a fault monitoring model for the equipments based on BP neural network. The equipment status and influencing factors were gained by wireless sensors. The model was used to determine whether the equipment worked normally, accurately diagnose the fault parts. The goal of intelligent inspection work was implemented. Finally, the air conditioning equipment was simulated to verify the validity of the model.