The invention discloses a fuzzy-intelligence-based rail traffic car suspension system fault analysis method. The method comprises the steps that 1, a rail traffic car suspension system model is constructed, and dynamic characteristic analysis is performed on the model; 2, according to the dynamic characteristic analysis result of the rail traffic car suspension system model, an acceleration sensor is arranged; 3, multiple data time domain and frequency domain characteristics collected by the acceleration sensor are extracted, and distance characteristics are extracted through power spectrum analysis; 4, dimension reduction processing is performed on an original characteristic sample in the step 3, and a fault characteristic sample is obtained; 5, on the basis of the fault characteristic sample, fuzzy intelligence is utilized for performing fault classification on the car suspension system. According to the scheme, the defect that time frequency domain characteristic indexes describe signal changes from a certain aspect of a time domain or a frequency domain is overcome, meanwhile, meanwhile, the defects that time frequency domain characteristic indexes are easily added and average calculating operation submerge difference characteristics are obtained are overcome, and the characteristic sample quality is improved.