This paper presents a dynamic diagnostic strategy based on reliability analysis and distance-based VIKOR with heterogeneous information. Specifically, the proposed method uses a dynamic fault tree (DFT) to describe the dynamic fault characteristics and evaluates the failure rate of components using interval numbers to deal with the epistemic uncertainty. Furthermore, DFT is mapped into a dynamic evidential network (DEN) to calculate some reliability parameters and these parameters together with test cost constitute a decision matrix. In addition, a dynamic diagnostic strategy is developed based on an improved VIKOR algorithm and the previous diagnosis result. This diagnosis algorithm determines the weights of attributes based on the Entropy concept to avoid experts’ subjectivity and obtains the optimal ranking directly on the original heterogeneous information without a transformation process, which can improve diagnosis efficiency and reduce information loss. Finally, the performance of the proposed method is evaluated by applying it to a train-ground wireless communication system. The results of simulation analysis show the feasibility and effectiveness of this methodology