The invention relates to a two-phase flow multi-element information fusion method based on a complex network and depth learning and application thereof. Complex networks are constructed for multi-channel time sequences obtained by a cycle-excitation dual-mode sensor; for each multi-channel time sequence obtained by the cycle-excitation dual-mode sensor, a weighted correlation coefficient complex network and a weight-free correlation coefficient complex network are established respectively to obtain a network index, and the network indexes are combined to form a feature vector; and depth learning model training and phase volume fraction measurement are carried out to obtain a depth learning module capable of realizing dual-mode multi-element information fusion. The cycle-excitation dual-mode sensor formed by a cycle-excitation multi-electrode conductivity sensor and a cycle-excitation multi-electrode capacitive sensor is used for carrying out a vertical oil-water two-phase flow experiment; the ratio of the oil phase to the water phase is fixed; and the experiment is carried out by changing the flows of the oil phase to the water phase. Therefore, the phase volume fraction of the two-phase flow is measured.