A soft-sensing method of gas/liquid mass flow- rate based on hybrid feedback (HF) Elman wavelet neural network

In industry, gas/liquid two-phase flow in horizontal pipe is very common in many industry processes, and their measurements are of significance. In our works, a series of gas/water two-phase flow experiments in a horizontal pipe were conducted in which the V-cone differential pressure meter was used, and a soft-sensing method was brought forward in which the hybrid feedback (HF) Elman wavelet neural network was developed to achieve the gas/water mass flow-rate. Experimental results showed that the soft-sensing method combined V-cone with the HF Elman wavelet network could satisfy the demand of gas/liquid mass flow-rate measurement and the error of the mass flow-rate was small. The test results show the adaptability of the HF Elman wavelet network is better. The method is attractive for possible applications in measurement.