To explore the process and evolution of large-scale flight delay propagation, and avoid previous research mainly focusing on observing real data and the distribution of delay propagation networks. Drawing inspiration from the classic susceptible-explored-infected-recovered(SEIR) model and taking into account the impact of node closure on large-scale flight delays. Based on this, the state of airport nodes was added to five categories, and a large-scale flight delay propagation model based on susceptible-explored-infected-death-recovered(SEIDR) was constructed and applied to air traffic networks. Using a combination of phase trajectory analysis and related parameter analysis, the propagation threshold and propagation law of large-scale flight delays were obtained, and the influence of propagation parameters between airport nodes on the propagation law of large-scale flight delays was further analyzed. Finally, a large-scale flight delay in 2022 was taken as an example for analysis and verification. The results show that the established model can more accurately describe the evolution process and propagation law of large-scale flight delays.