The invention discloses a big data analysis system for a monitoring state of railway automatic fare collection equipment. The system comprises a base layer, a management layer, an analysis layer and an application layer. Along with the increase of an installation quantity of the automatic fare collection equipment, the developmental key of an existing automatic fare collection system is to improvethe system stability and shorten and reduce the maintenance time and cost by adopting fault analysis and early warning means through fully utilizing existing automatic fare collection service data. In order to solve the problems that the complex problem is difficult to locate and the experience of maintenance personnel is excessively relied on for manual handling in maintenance operation of an automatic fare collection network, response time data of the system is subjected to clustering analysis, and a big data technology is adopted for effectively finding out fault rules from the mass data of the system and mining relations between faults and a system environment and between the faults and user behaviors, so that the effects of improving the monitoring level of the system and ensuring the normal operation of the automatic fare collection system are achieved.