The microswitch is a common switchgear of the railway vehicle driver controller, and the evaluation of its health condition is the prerequisite to ensure the safety of railway vehicle operation. Aiming at the problem that the data of the controller microswitch is few, the signal is nonlinear, and the health status is difficult to assess, a method for evaluating the health status of microswitch based on the belief rule base(BRB) is proposed. Firstly, the relation between the failure mechanism and the fault characteristics of the microswitch is analyzed, and the qualitative knowledge and quantitative information are effectively combined with the BRB, the knowledge is reasoned by using the evidential reasoning(ER) algorithm, the initial parameters of the model are optimized, and the optimal set of parameters is obtained, which improves the accuracy of evaluating the health status of the microswitch. Through the training and testing of the model, the experimental results show that the method can accurately evaluate the fault of the microswitch in railway vehicle, which is convenient to detect faults early, track the development trend of failure and replace the failed components in a timely manner.