To improve the efficiency of constructing concept lattices, we propose an incremental concept lattice construction method based on granular concept network in this paper. The proposed method explores the update mechanism of granular concept network in the formal context where attributes are constantly increasing. Specifically, the updating mechanism of concepts in each layer of the granular concept network was first explored, and then new concept nodes were generated through cross level concept fusion strategy to achieve incremental expansion of the network structure. Furthermore, the concept lattice of updated formal context was generated from the granular concept network. Finally, the effectiveness of the method proposed in this paper was verified through numerical experiments in terms of concept acquisition task.