The invention relates to an intelligent substation secondary system state analysis method based on a fuzzy C-mean clustering algorithm. The intelligent substation secondary system state analysis method has the advantages that by establishing a defect database, a database comprising the defect type, the highest equipment operating temperature, the light transmitting power, the receiving sensitivity and the equipment ground insulation resistance value when secondary equipment is in failure is found out from a large number of equipment operating conditions, the load data, various state detection data, the defect information, the failure and accident information and the overhaul data of a production management system, a secondary equipment operation management accounting system and other systems of a power system. The operating state of a substation secondary system can be obtained in real time, so that the maintenance can be performed before the occurrence of a problem.