Abstract: The accurate characterization of switching device state is the necessary premise to realize its high intelligent development. In view of the fact that the whole life of switching device is dynamic and changing randomly with multiplicity, multi-state and multi-attributes interaction, taking multi-attribute characteristic parameters as the driving force and fully considering the effects weight and dynamic correlation of parameters, the new state space, in other words the modal space, was reconstructed through characteristic transformation, and the weighted improvement of common similarity measurement method was proposed. Then, the basic mode of switching device was taken as the parameter, and the modal similarity measurement was used to quantitatively characterize the switching device state, thus the time series characterization model was established, and in this way the dynamic characterization of the real-time state of the switch device was realized. Finally, through the verification and analysis of the measured data, the results show that the proposed method is effective and feasible, and can realize the dynamic analysis and quantitative characterization of the whole life cycle state of switching devices. At the same time, compared with two similar methods, the results showed that the proposed method has a higher characterization accuracy in the state characterization of contact switching devices, which provides a reference for the accurate prediction and dynamic identification of switching device state in the next step of research.