Abstract: This study investigates the identification of peak efficiency operation in airlift pump through experimental pressure signal analysis. Pressure measurements were collected from multiple sensors located along the riser pipe to characterize gas-liquid two-phase flow across various flow regimes. Power spectral density and wavelet packet decomposition were used to analyze the pressure signals and reveal the relationship between airlift pump efficiency and flow regime transitions. The results show that during the slug flow period, when the pressure signal collected by the sensor in the middle of the pipeline reaches a peak in energy proportion within the 0–32 Hz frequency band and the corresponding singular spectrum entropy is at a low valley value, it indicates that the interaction between the gas and liquid phases in the system is in an optimal state, and the pump efficiency reaches its maximum value. Experimental validation confirms that the characteristics of the pressure signal can effectively identify whether the airlift pump is at its efficiency peak under the current gas superficial velocity. This study provides new ideas and methods for monitoring airlift pump efficiency based on pressure signals, offering significant practical value.