ect and ls-svm based void fraction measurement of oil-gas two-phase flow

a method based on electrical capacitance tomography (ect) and an improved least squares support vector machine (ls-svm) is proposed for void fraction measurement of oil-gas two-phase flow. in the modeling stage, to solve the two problems in ls-svm, pruning skills are employed to make ls-svm sparse and robust; then the real-coded genetic algorithm is introduced to solve the difficult problem of parameters selection in ls-svm then. in the measurement process, the flow pattern of oil-gas two-phase flow is identified by using fast back-projection image reconstruction and a fuzzy pattern recognition technique and the void fraction is computed using the void fraction model corresponding to the identified flow pattern. experimental results demonstrate that both the improvement of ls-svm and the parameter optimization are effective. the results also show that the real-time performance of the proposed void fraction measurement method is good, and the measurement precision can satisfy the application requirement.