Fault detecting method for train suspension system of data driving based on acceleration measuring

The invention relates to a fault detecting method for a train suspension system of data driving based on acceleration measuring. The method includes the following steps: (1) acceleration signals of various positions during operation of a train are obtained through acceleration sensors; (2) anti-aliasing filtering, high-pass filtering and secondary integral pre-processing are conducted on the acceleration signals, and system output, namely displacement signals of positions of the sensors, is obtained; (3) a statistic model of the system is built through a dynamic primary component analysis (DPCA) algorithm; (4) the system output in the step (2) is obtained in real time, and a T2 index and an SPE index of monitoring signals are calculated in real time according to the statistic model in the step (3); and (5) whether the monitoring signals exceed a set threshold is judged, when any one of the two monitoring indexes exceed the threshold, fault alarming is conducted. The detecting method is easy to popularize and apply; is good in fault sensitivity and capable of detecting weak faults of the train suspension system; and is short in fault detect responding time and can detect faults fast after the faults occur.