The acoustic emission (AE) signal characteristics under different operation conditions of packed column were investigated by analyzing standard deviation (STD)

power spectrum density (PSD) and multi-scale wavelet transform of acoustic emission signals. Criterions to determine the flooding gas velocity were proposed. The influence of liquid flowrate was investigated by air-water experiments. It was found that the prediction of the flooding gas velocity by AE signal STD was close to that by pressure drop. The power spectrum density of acoustic emission signals under different operation conditions showed that the maximal PSD peak transferred from around 50 kHz and 60 kHz to around 25 kHz when the packed column flooding. 7 scales wavelet transform was used to investigate the acoustic emission signals. Energy fraction of G1 (d4

d5) scale had a sharp rise as the gas velocity came to flooding gas velocity. The prediction of flooding gas velocity by G1 scale energy fraction was close to that by pressure drop. As a non-invasive method

acoustic emission detection can monitor flooding accurately and have a good application prospect.