The seismic wave signal acquisition will result in the mixed noise in the measured signal due to the monitoring environment, test system and other factors, and the existence of noise will lead to the distortion of the time-frequency analysis results of the signal Hilbert-Huang Transform. There are two reasons. One is that the empirical mode decomposition (EMD) algorithm will obtain the intrinsic mode function (IMF) component with modal confusion phenomenon when processing the blasting seismic wave signal containing noise; The other reason is that because the Hilbert transform is constrained by the Bedrosian theorem, which will produce negative instantaneous frequencies when dealing with modal confusion components. These lead to huge analytical errors. In order to obtain real blasting vibration properties, HHT should be improved. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) can be obtained by adding adaptive noise signal to EMD. Then normalized Hilbert transform is performed on the IMF obtained by CEEMDAN, and an improved normalized Hilbert transform (INHT) is obtained. Through the above two steps, the CEEMDAN-INHT time-frequency analysis algorithm can be established. In order to verify that the algorithm can effectively improve the time-frequency analysis accuracy of the noise-containing blasting seismic wave vibration signal, a comparative study on the time-frequency analysis of the HHT and CEEMDAN-INHT noise-containing simulated vibration signals is carried out. Finally, CEEMDAN-INHT is used in the time-frequency analysis of blasting seismic wave signals in an underground cavern, and it is found that the algorithm can effectively overcome the inherent mode confusion of EMD, and at the same time obtain the time-frequency-energy characteristic parameters reflecting the real blasting vibration attributes. It is of practical significance to carry out resonance analysis of blasting excavation in caverns from the perspective of frequency and energy, and to realize blasting seismic wave hazard control.