Abstract
With the rapid development of economy and urbanization, subway has gradually become the main pillar of urban development. The ventilation system is the key guarantee of air quality in rail transit, and its condition monitoring and intelligent diagnosis are very important. The core problems of the complete set of a ventilation system required by the subway station have not been completely solved. The ventilation system includes the ventilator and additional equipment. The level of informatization and intelligence of the ventilation system and ventilator is not very high, and they have not yet been fully formed into an integrated diagnostic system. In view of the above two core issues, several scientific issues need to be tackled. This chapter studies the online monitoring and intelligent diagnosis mechanism of key equipment in the subway ventilation system. This mainly includes (1) modulation model of acoustic vibration signal; (2) noise reduction technology and feature extraction method; and (3) cases of multi-type typical fault identification fan equipment based on modulation model. Typical fault features were extracted respectively, which verified the effectiveness of the signal demodulation method for the diagnosis of rail transit ventilation systems.