Abstract
The suspension system is one of the key components of the city rail train, whose status is directly related to the comfort, reliability, and security of the train. Urban rail train suspension system generally uses passive detection; the detection is achieved mainly by artificial periodic inspection, which wastes manpower, material, and financial resources. This paper uses the PLS (partial least squares) algorithm to perform the fault detection experiment of suspension system of urban rail vehicle under track irregularity. Under the effect of track irregularity, the experiment of suspension system of urban rail vehicle is carried out using the D–S (Dempster–Shafer) evidence theory. The research results show that the PLS algorithm can be used for fault detection in transit and fault warning, to ensure driving safety. D–S evidence theory can completely separate the fault component type.
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