In order to realize online monitoring of particle concentration in gas-solid two-phase flow in pipe

the sensor installed on a wire mesh interface was applied to collect the acoustic emission(AE) signals of gas-liquid two phase flow with different particle concentrations. The signal was then decomposed by ensemble empirical mode decomposition(EEMD) algorithm

and the contribution ratio and frequency domain characteristics of the energy of the intrinsic mode function(IMF) was compared with the original signals. The linear relationship between the particle concentrations and IMFs was built up and then verified by actual cases. The results illustrate that

at the solid flow rate of 4 g/s to 20 g/s

all the IMF1

IMF2 and IMF3 components can well reflect the characteristics of some frequency of the original signals

indicating they can be used to build the relationship between particle concentration and the acoustic emission signal. The error of the fitting function is lower than 10% and the average error is lower than 5%. Compared with the wavelet packet decomposition(WPD) method

the results obtained by the EEMD method are more accurate. Therefore

the three components decomposed by the EEMD are suitable for monitoring the particle concentration in the gas-solid two-phase flow.